This document discusses an improved weighted least squares (WLS) filter-based pan sharpening method using fuzzy logic. It aims to address limitations of prior work by integrating an improved principal component analysis (PCA) algorithm with fuzzy logic for image fusion. The proposed algorithm is implemented in MATLAB using image processing toolbox. Comparative analysis shows the effectiveness of the proposed algorithm based on various performance metrics. It combines useful information from multi-focus images to generate a fused image with better quality.
Performance of Weighted Least Square Filter Based Pan Sharpening using Fuzzy ...IRJET Journal
This document proposes a new algorithm for pan sharpening images that combines weighted least squares filtering with fuzzy logic. It summarizes previous research on image fusion techniques like principal component analysis and discrete cosine transformation. The proposed algorithm applies fuzzy logic to evaluate membership functions and attain a pan sharpened image. It then uses a weighted least squares filter for pan sharpening. The algorithm is implemented in MATLAB and evaluated based on metrics like root mean square error, peak signal-to-noise ratio, and mean square error. Results show the proposed technique improves upon existing methods by reducing errors and increasing quality measurements of the fused images.
Contrast Enhancement Techniques: A Brief and Concise ReviewIRJET Journal
The document discusses various contrast enhancement techniques for digital images. It provides an overview of techniques such as histogram equalization, which works by flattening the histogram and stretching the dynamic range of gray levels. Global histogram equalization uses the entire image histogram for contrast adjustment, while local histogram equalization processes the image in blocks to better preserve local details and brightness levels. The techniques aim to improve image quality by increasing luminance differences between foreground and background.
IRJET - Review of Various Multi-Focus Image Fusion MethodsIRJET Journal
This document provides an overview of multi-focus image fusion methods. It discusses various multi-focus image fusion techniques in both the spatial and frequency domains. It reviews several papers on multi-focus image fusion using different methods like region mosaicking on laplacian pyramid (RMLP), discrete wavelet transform (DWT), principal component analysis (PCA), discrete cosine transform (DCT), and implementation on field programmable gate arrays (FPGAs). The document compares the advantages and issues of the techniques discussed in the reviewed papers. It provides context on applications of image fusion in areas like remote sensing, medical imaging, and more.
A comprehensive method for image contrast enhancement based on global –local ...eSAT Publishing House
This document presents a method for image contrast enhancement based on combining global and local contrast techniques. It addresses issues with existing local standard deviation based methods when applied to constant image areas, which results in divided by zero errors. The proposed method modifies the local standard deviation calculation by adding a small value to avoid this, allowing contrast enhancement to be applied across the entire image without information loss. Experimental results on test images demonstrate improved contrast enhancement over existing methods, as measured by peak signal-to-noise ratio values.
Image Contrast Enhancement Approach using Differential Evolution and Particle...IRJET Journal
This document presents a method for enhancing the contrast of gray-scale images using differential evolution optimization. It proposes using a parameterized intensity transformation function to modify pixel gray levels, with the goal of maximizing image contrast. The differential evolution algorithm is used to optimize the parameters of the transformation function. Experimental results applying this method are compared to other contrast enhancement techniques like histogram equalization and particle swarm optimization. The document provides background on image enhancement techniques, a literature review of previous work applying evolutionary algorithms like particle swarm optimization to image enhancement, and details of the proposed differential evolution approach, including the transformation function and fitness function used to evaluate contrast.
This document reviews different techniques for thinning images, including the Zhang and Suen algorithm and neural networks. It provides an overview of existing thinning approaches, such as iterative algorithms, and proposes a new approach using neural networks. The proposed approach aims to perform thinning invariant to rotations while being less sensitive to noise than existing methods. It evaluates techniques based on execution time, thinning rate, and other performance measures. The document concludes that neural networks may provide better results than existing techniques in terms of metrics like PSNR and MSE, while also reducing execution time for skeletonization.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
A Review of Image Contrast Enhancement TechniquesIRJET Journal
This document reviews several techniques for image contrast enhancement. It begins with an introduction to image enhancement and its goals of improving visual appearance and clarity. The paper then surveys key approaches for contrast enhancement including histogram equalization, discrete wavelet transform, and other spatial and frequency domain methods. Finally, the conclusion is that contrast enhancement using digital image processing continues to be an active area of research that can help solve problems across many fields involving image analysis.
Performance of Weighted Least Square Filter Based Pan Sharpening using Fuzzy ...IRJET Journal
This document proposes a new algorithm for pan sharpening images that combines weighted least squares filtering with fuzzy logic. It summarizes previous research on image fusion techniques like principal component analysis and discrete cosine transformation. The proposed algorithm applies fuzzy logic to evaluate membership functions and attain a pan sharpened image. It then uses a weighted least squares filter for pan sharpening. The algorithm is implemented in MATLAB and evaluated based on metrics like root mean square error, peak signal-to-noise ratio, and mean square error. Results show the proposed technique improves upon existing methods by reducing errors and increasing quality measurements of the fused images.
Contrast Enhancement Techniques: A Brief and Concise ReviewIRJET Journal
The document discusses various contrast enhancement techniques for digital images. It provides an overview of techniques such as histogram equalization, which works by flattening the histogram and stretching the dynamic range of gray levels. Global histogram equalization uses the entire image histogram for contrast adjustment, while local histogram equalization processes the image in blocks to better preserve local details and brightness levels. The techniques aim to improve image quality by increasing luminance differences between foreground and background.
IRJET - Review of Various Multi-Focus Image Fusion MethodsIRJET Journal
This document provides an overview of multi-focus image fusion methods. It discusses various multi-focus image fusion techniques in both the spatial and frequency domains. It reviews several papers on multi-focus image fusion using different methods like region mosaicking on laplacian pyramid (RMLP), discrete wavelet transform (DWT), principal component analysis (PCA), discrete cosine transform (DCT), and implementation on field programmable gate arrays (FPGAs). The document compares the advantages and issues of the techniques discussed in the reviewed papers. It provides context on applications of image fusion in areas like remote sensing, medical imaging, and more.
A comprehensive method for image contrast enhancement based on global –local ...eSAT Publishing House
This document presents a method for image contrast enhancement based on combining global and local contrast techniques. It addresses issues with existing local standard deviation based methods when applied to constant image areas, which results in divided by zero errors. The proposed method modifies the local standard deviation calculation by adding a small value to avoid this, allowing contrast enhancement to be applied across the entire image without information loss. Experimental results on test images demonstrate improved contrast enhancement over existing methods, as measured by peak signal-to-noise ratio values.
Image Contrast Enhancement Approach using Differential Evolution and Particle...IRJET Journal
This document presents a method for enhancing the contrast of gray-scale images using differential evolution optimization. It proposes using a parameterized intensity transformation function to modify pixel gray levels, with the goal of maximizing image contrast. The differential evolution algorithm is used to optimize the parameters of the transformation function. Experimental results applying this method are compared to other contrast enhancement techniques like histogram equalization and particle swarm optimization. The document provides background on image enhancement techniques, a literature review of previous work applying evolutionary algorithms like particle swarm optimization to image enhancement, and details of the proposed differential evolution approach, including the transformation function and fitness function used to evaluate contrast.
This document reviews different techniques for thinning images, including the Zhang and Suen algorithm and neural networks. It provides an overview of existing thinning approaches, such as iterative algorithms, and proposes a new approach using neural networks. The proposed approach aims to perform thinning invariant to rotations while being less sensitive to noise than existing methods. It evaluates techniques based on execution time, thinning rate, and other performance measures. The document concludes that neural networks may provide better results than existing techniques in terms of metrics like PSNR and MSE, while also reducing execution time for skeletonization.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
A Review of Image Contrast Enhancement TechniquesIRJET Journal
This document reviews several techniques for image contrast enhancement. It begins with an introduction to image enhancement and its goals of improving visual appearance and clarity. The paper then surveys key approaches for contrast enhancement including histogram equalization, discrete wavelet transform, and other spatial and frequency domain methods. Finally, the conclusion is that contrast enhancement using digital image processing continues to be an active area of research that can help solve problems across many fields involving image analysis.
A Survey on Image Retrieval By Different Features and TechniquesIRJET Journal
This document discusses various techniques for content-based image retrieval. It begins with an introduction to content-based image retrieval and describes how it uses visual features like color, texture, shape and regions to index and represent image content for retrieval. The document then reviews related work on image retrieval using different features. It discusses features used for image identification like color, edges, corners and texture. The document also outlines techniques for image retrieval including relevance feedback, support vector machines, block truncation coding, and image clustering. Finally, it evaluates parameters for comparing image retrieval algorithms.
Comprehensive Performance Comparison of Cosine, Walsh, Haar, Kekre, Sine, Sla...CSCJournals
This document presents a comparison of various image transforms for content-based image retrieval (CBIR) using fractional coefficients of transformed images. It proposes CBIR techniques that extract features from images transformed using discrete cosine, Walsh, Haar, Kekre, discrete sine, slant, and discrete Hartley transforms. Features are extracted from the gray-scale and individual color planes of images. Fractional coefficients, representing percentages of the full transformed image, are used to reduce feature vector size and speed up retrieval times compared to using the full transform. The techniques are tested on a database of 1000 images from 11 categories, and results show the Kekre transform achieves the best precision and recall, outperforming other transforms when using 6
Abstract: Many applications such as robot navigation, defense, medical and remote sensing performvarious processing tasks, which can be performed more easily when all objects in different images of the same scene are combined into a single fused image. In this paper, we propose a fast and effective method for image fusion. The proposed method derives the intensity based variations that is large and small scale, from the source images. In this approach, guided filtering is employed for this extraction. Gaussian and Laplacian pyramidal approach is then used to fuse the different layers obtained. Experimental results demonstrate that the proposed method can obtain better performance for fusion of
all sets of images. The results clearly indicate the feasibility of the proposed approach.
Enhancement of Medical Images using Histogram Based Hybrid TechniqueINFOGAIN PUBLICATION
Digital Image Processing is very important area of research. A number of techniques are available for image enhancement of gray scale images as well as color images. They work very efficiently for enhancement of the gray scale as well as color images. Important techniques namely Histogram Equalization, BBHE, RSWHE, RSWHE (recursion=2, gamma=No), AGCWD (Recursion=0, gamma=0) have been used quite frequently for image enhancement. But there are some shortcomings of the present techniques. The major shortcoming is that while enhancement, the brightness of the image deteriorates quite a lot. So there was need for some technique for image enhancement so that while enhancement was done, the brightness of the images does not go down. To remove this shortcoming, a new hybrid technique namely RESWHE+AGCWD (recursion=2, gamma=0 or 1) was proposed. The results of the proposed technique were compared with the existing techniques. In the present methodology, the brightness did not decrease during image enhancement. So the results and the technique was validated and accepted. The parameters via PSNR, MSE, AMBE etc. are taken for performance evaluation and validation of the proposed technique against the existing techniques which results in better outperform.
Spectral approach to image projection with cubic b spline interpolationiaemedu
This document summarizes a research paper that proposes a new method for image projection using spectral interpolation with cubic B-spline interpolation. The key points are:
1) Existing super resolution methods based on Fourier transforms have limitations in providing high visual quality when scaling images.
2) The proposed method first transforms image frames into the frequency domain using FFT. It then interpolates in the spectral domain using cubic B-spline interpolation to project the images onto a higher resolution grid.
3) Experimental results show the proposed method provides higher visual quality projections compared to conventional Fourier-based approaches, while also having faster computation times.
An Improved Way of Segmentation and Classification of Remote Sensing Images U...ijsrd.com
The Ultimate significance of Images lies in processing the digital image which stems from two principal application areas: Advances of pictorial information for human interpretation; and dispensation of image data for storage, communication, and illustration for self-sufficient machine perception. The objective of this research work is to define the meaning and possibility of image segmentation based on remote sensing images which are successively classified with statistical measures. In this paper kernel induced Possiblistic C-means clustering algorithm has been implemented for classifying remote sensing image data with image features. As a final point of the proposed work is to point out that this algorithm works well for segmenting and classifying the image with better accuracy with statistical metrices.
A Novel Approach To Detection and Evaluation of Resampled Tampered ImagesCSCJournals
Most digital forgeries use an interpolation function, affecting the underlying statistical distribution of the image pixel values, that when detected, can be used as evidence of tampering. This paper provides a comparison of interpolation techniques, similar to Lehmann [1], using analyses of the Fourier transform of the image signal, and a quantitative assessment of the interpolation quality after applying selected interpolation functions, alongside an appraisal of computational performance using runtime measurements. A novel algorithm is proposed for detecting locally tampered regions, taking the averaged discrete Fourier transform of the zero-crossing of the second difference of the resampled signal (ADZ). The algorithm was contrasted using precision, recall and specificity metrics against those found in the literature, with comparable results. The interpolation comparison results were similar to that of [1]. The results of the detection algorithm showed that it performed well for determining authentic images, and better than previously proposed algorithms for determining tampered regions.
IRJET- Crowd Density Estimation using Image ProcessingIRJET Journal
This document describes a research project that uses image processing techniques to estimate crowd density. Specifically, it uses skin color detection and morphological operations to identify and count the number of people in an image. It begins with an abstract that introduces the topic and objectives. It then provides background information on relevant color models and traditional crowd density estimation approaches. The proposed system is described as using skin color detection in the HSV color space to identify skin pixels, followed by morphological operations to find and count human faces, in order to efficiently and accurately estimate crowd density in images.
Stereo matching based on absolute differences for multiple objects detectionTELKOMNIKA JOURNAL
This article presents a new algorithm for object detection using stereo camera system. The problem to get an accurate object detion using stereo camera is the imprecise of matching process between two scenes with the same viewpoint. Hence, this article aims to reduce the incorrect matching pixel with four stages. This new algorithm is the combination of continuous process of matching cost computation, aggregation, optimization and filtering. The first stage is matching cost computation to acquire preliminary result using an absolute differences method. Then the second stage known as aggregation step uses a guided filter with fixed window support size. After that, the optimization stage uses winner-takes-all (WTA) approach which selects the smallest matching differences value and normalized it to the disparity level. The last stage in the framework uses a bilateral filter. It is effectively further decrease the error on the disparity map which contains information of object detection and locations. The proposed work produces low errors (i.e., 12.11% and 14.01% nonocc and all errors) based on the KITTI dataset and capable to perform much better compared with before the proposed framework and competitive with some newly available methods.
Image segmentation by modified map ml estimationsijesajournal
Though numerous algorithms exist to perform image segmentation there are several issues
related to execution time of these algorithm. Image Segmentation is nothing but label relabeling
problem under probability framework. To estimate the label configuration, an iterative
optimization scheme is implemented to alternately carry out the maximum a posteriori (MAP)
estimation and the maximum likelihood (ML) estimations. In this paper this technique is
modified in such a way so that it performs segmentation within stipulated time period. The
extensive experiments shows that the results obtained are comparable with existing algorithms.
This algorithm performs faster execution than the existing algorithm to give automatic
segmentation without any human intervention. Its result match image edges very closer to
human perception.
Visual Cryptography using Image ThresholdingIRJET Journal
This document proposes a novel visual cryptography algorithm using image thresholding that generates shares of an image without requiring a key. The technique thresholds the secret image to create two shares such that individual shares do not reveal information about the secret image. The original image can be reconstructed by performing an OR operation on the pixel values of the shares using the threshold value, without any loss of quality or information. The algorithm was tested on color images in MATLAB and successfully recovered the original image from the shares.
Brain tumor segmentation using asymmetry based histogram thresholding and k m...eSAT Publishing House
This document presents a method for segmenting brain tumors from MRI images using asymmetry-based histogram thresholding and k-means clustering. The method involves 8 steps: 1) preprocessing the MRI image using sharpening and median filters, 2) computing histograms of the left and right halves of the image, 3) calculating a threshold value using the difference between left and right histograms, 4) applying thresholding and morphological operations to extract the tumor region, 5) applying k-means clustering and using the cluster centroids to refine the segmentation. The method is tested on 30 MRI images and results show the tumor region is accurately segmented. The segmented tumors can then be used for quantification, classification, and computer-assisted diagnosis of brain tumors.
IRJET- Saliency based Image Co-SegmentationIRJET Journal
The document describes a saliency-based image co-segmentation method. It proposes to first extract inter-image information through co-saliency maps generated from multiple saliency extraction methods. Then, it performs single image segmentation on each individual image. A key step is fusing the diverse saliency maps through a saliency co-fusion process at the superpixel level. This exploits inter-image information to boost common foreground regions and suppress background regions. Experiments show the co-fusion based approach achieves competitive performance compared to state-of-the-art methods without parameter tuning.
IRJET- Digital Image Forgery Detection using Local Binary Patterns (LBP) and ...IRJET Journal
This document proposes a method to detect digital image forgeries using local binary patterns (LBP) and histogram of oriented gradients (HOG). It extracts LBP features from the input image, then applies HOG to the LBP features. These combined features are classified using a support vector machine (SVM) as authentic or tampered. Testing on CASIA datasets achieved detection rates of 92.3% for CASIA-1 and 96.1% for CASIA-2, outperforming other existing methods. The method is effective at forgery detection while having reduced time complexity.
There exists a plethora of algorithms to perform image segmentation and there are several issues related to
execution time of these algorithms. Image Segmentation is nothing but label relabeling problem under
probability framework. To estimate the label configuration, an iterative optimization scheme is
implemented to alternately carry out the maximum a posteriori (MAP) estimation and the maximum
likelihood (ML) estimations. In this paper this technique is modified in such a way so that it performs
segmentation within stipulated time period. The extensive experiments shows that the results obtained are
comparable with existing algorithms. This algorithm performs faster execution than the existing algorithm
to give automatic segmentation without any human intervention. Its result match image edges very closer to
human perception.
This document compares image enhancement and analysis techniques using image processing and wavelet techniques on thermal images. It discusses various image enhancement methods such as converting images to grayscale, histogram equalization, contrast enhancement, linear and adaptive filtering, morphology, FFT transforms, and wavelet-based techniques including image fusion, denoising, and compression. Results showing enhanced, denoised, and compressed images are presented and analyzed. The document concludes that wavelet techniques provide better enhancement of thermal images compared to traditional image processing methods.
A DISCUSSION ON IMAGE ENHANCEMENT USING HISTOGRAM EQUALIZATION BY VARIOUS MET...pharmaindexing
This document summarizes several papers on image enhancement techniques using histogram equalization. It discusses papers that propose sub-region histogram equalization to improve contrast while preserving spatial relationships. It also discusses a 3D histogram equalization method that produces a uniform 1D grayscale histogram to overcome issues with previous color histogram methods. Another paper proposes using total variation minimization for cartoon-texture decomposition prior to histogram equalization to reduce intensity saturation effects. Further, a technique called gain controllable clipped histogram equalization is presented to enhance contrast while preserving original brightness. Finally, a method called bi-histogram equalization with neighborhood metrics is described which divides histograms to improve local contrast while maintaining brightness.
The Computation Complexity Reduction of 2-D Gaussian FilterIRJET Journal
This document discusses reducing the computational complexity of a 2D Gaussian filter for image smoothing. It begins with an abstract that notes 2D Gaussian filters are commonly used for image smoothing but require heavy computational resources. It then proposes using fixed-point arithmetic rather than floating point to implement the filter on an FPGA, which can increase efficiency and decrease area and complexity. The document is divided into sections that cover the theory behind image filtering, image smoothing and sharpening, quality metrics for evaluation, and an energy scalable Gaussian smoothing filter architecture. It concludes by discussing results and benefits of implementing the filter using fixed-point arithmetic on an FPGA.
IRJET- An Improvised Multi Focus Image Fusion Algorithm through QuadtreeIRJET Journal
The document proposes a new quadtree-based algorithm for multi-focus image fusion. The algorithm divides the input images into 4 equal blocks using a quadtree structure. It then further divides each block into smaller blocks and detects the focused regions in each block using a focus measure and weighted values. The small blocks are then fused using a modified Laplacian mechanism. The fused image is evaluated using SSIM and ESSIM values, which indicate the proposed algorithm performs better fusion than previous methods.
IRJET- A Plant Identification and Recommendation SystemIRJET Journal
This document describes a plant identification and recommendation system that uses image recognition techniques. The system takes an image of a leaf as input, preprocesses it by resizing, converting to grayscale, and extracting features. It then uses a convolutional neural network with the Inception-v3 model to identify the plant by comparing features to those in its database. Based on the identified plant, it recommends other plants that could grow in that location. The system is implemented as both a mobile app and web application to be accessible anywhere.
IRJET - Symmetric Image Registration based on Intensity and Spatial Informati...IRJET Journal
This document presents a proposed system for symmetric image registration based on intensity and spatial information using a technique called the Coloured Simple Algebraic Algorithm (CSAA). The system first preprocesses color images, extracts features, then classifies images as symmetric or asymmetric using a neural network. It is shown to provide accurate and robust registration of medical and biomedical images. The system is implemented and evaluated on sample images, demonstrating it can successfully identify symmetric versus asymmetric images. The proposed approach aims to improve on existing techniques for intensity-based image registration tasks.
A Survey on Image Retrieval By Different Features and TechniquesIRJET Journal
This document discusses various techniques for content-based image retrieval. It begins with an introduction to content-based image retrieval and describes how it uses visual features like color, texture, shape and regions to index and represent image content for retrieval. The document then reviews related work on image retrieval using different features. It discusses features used for image identification like color, edges, corners and texture. The document also outlines techniques for image retrieval including relevance feedback, support vector machines, block truncation coding, and image clustering. Finally, it evaluates parameters for comparing image retrieval algorithms.
Comprehensive Performance Comparison of Cosine, Walsh, Haar, Kekre, Sine, Sla...CSCJournals
This document presents a comparison of various image transforms for content-based image retrieval (CBIR) using fractional coefficients of transformed images. It proposes CBIR techniques that extract features from images transformed using discrete cosine, Walsh, Haar, Kekre, discrete sine, slant, and discrete Hartley transforms. Features are extracted from the gray-scale and individual color planes of images. Fractional coefficients, representing percentages of the full transformed image, are used to reduce feature vector size and speed up retrieval times compared to using the full transform. The techniques are tested on a database of 1000 images from 11 categories, and results show the Kekre transform achieves the best precision and recall, outperforming other transforms when using 6
Abstract: Many applications such as robot navigation, defense, medical and remote sensing performvarious processing tasks, which can be performed more easily when all objects in different images of the same scene are combined into a single fused image. In this paper, we propose a fast and effective method for image fusion. The proposed method derives the intensity based variations that is large and small scale, from the source images. In this approach, guided filtering is employed for this extraction. Gaussian and Laplacian pyramidal approach is then used to fuse the different layers obtained. Experimental results demonstrate that the proposed method can obtain better performance for fusion of
all sets of images. The results clearly indicate the feasibility of the proposed approach.
Enhancement of Medical Images using Histogram Based Hybrid TechniqueINFOGAIN PUBLICATION
Digital Image Processing is very important area of research. A number of techniques are available for image enhancement of gray scale images as well as color images. They work very efficiently for enhancement of the gray scale as well as color images. Important techniques namely Histogram Equalization, BBHE, RSWHE, RSWHE (recursion=2, gamma=No), AGCWD (Recursion=0, gamma=0) have been used quite frequently for image enhancement. But there are some shortcomings of the present techniques. The major shortcoming is that while enhancement, the brightness of the image deteriorates quite a lot. So there was need for some technique for image enhancement so that while enhancement was done, the brightness of the images does not go down. To remove this shortcoming, a new hybrid technique namely RESWHE+AGCWD (recursion=2, gamma=0 or 1) was proposed. The results of the proposed technique were compared with the existing techniques. In the present methodology, the brightness did not decrease during image enhancement. So the results and the technique was validated and accepted. The parameters via PSNR, MSE, AMBE etc. are taken for performance evaluation and validation of the proposed technique against the existing techniques which results in better outperform.
Spectral approach to image projection with cubic b spline interpolationiaemedu
This document summarizes a research paper that proposes a new method for image projection using spectral interpolation with cubic B-spline interpolation. The key points are:
1) Existing super resolution methods based on Fourier transforms have limitations in providing high visual quality when scaling images.
2) The proposed method first transforms image frames into the frequency domain using FFT. It then interpolates in the spectral domain using cubic B-spline interpolation to project the images onto a higher resolution grid.
3) Experimental results show the proposed method provides higher visual quality projections compared to conventional Fourier-based approaches, while also having faster computation times.
An Improved Way of Segmentation and Classification of Remote Sensing Images U...ijsrd.com
The Ultimate significance of Images lies in processing the digital image which stems from two principal application areas: Advances of pictorial information for human interpretation; and dispensation of image data for storage, communication, and illustration for self-sufficient machine perception. The objective of this research work is to define the meaning and possibility of image segmentation based on remote sensing images which are successively classified with statistical measures. In this paper kernel induced Possiblistic C-means clustering algorithm has been implemented for classifying remote sensing image data with image features. As a final point of the proposed work is to point out that this algorithm works well for segmenting and classifying the image with better accuracy with statistical metrices.
A Novel Approach To Detection and Evaluation of Resampled Tampered ImagesCSCJournals
Most digital forgeries use an interpolation function, affecting the underlying statistical distribution of the image pixel values, that when detected, can be used as evidence of tampering. This paper provides a comparison of interpolation techniques, similar to Lehmann [1], using analyses of the Fourier transform of the image signal, and a quantitative assessment of the interpolation quality after applying selected interpolation functions, alongside an appraisal of computational performance using runtime measurements. A novel algorithm is proposed for detecting locally tampered regions, taking the averaged discrete Fourier transform of the zero-crossing of the second difference of the resampled signal (ADZ). The algorithm was contrasted using precision, recall and specificity metrics against those found in the literature, with comparable results. The interpolation comparison results were similar to that of [1]. The results of the detection algorithm showed that it performed well for determining authentic images, and better than previously proposed algorithms for determining tampered regions.
IRJET- Crowd Density Estimation using Image ProcessingIRJET Journal
This document describes a research project that uses image processing techniques to estimate crowd density. Specifically, it uses skin color detection and morphological operations to identify and count the number of people in an image. It begins with an abstract that introduces the topic and objectives. It then provides background information on relevant color models and traditional crowd density estimation approaches. The proposed system is described as using skin color detection in the HSV color space to identify skin pixels, followed by morphological operations to find and count human faces, in order to efficiently and accurately estimate crowd density in images.
Stereo matching based on absolute differences for multiple objects detectionTELKOMNIKA JOURNAL
This article presents a new algorithm for object detection using stereo camera system. The problem to get an accurate object detion using stereo camera is the imprecise of matching process between two scenes with the same viewpoint. Hence, this article aims to reduce the incorrect matching pixel with four stages. This new algorithm is the combination of continuous process of matching cost computation, aggregation, optimization and filtering. The first stage is matching cost computation to acquire preliminary result using an absolute differences method. Then the second stage known as aggregation step uses a guided filter with fixed window support size. After that, the optimization stage uses winner-takes-all (WTA) approach which selects the smallest matching differences value and normalized it to the disparity level. The last stage in the framework uses a bilateral filter. It is effectively further decrease the error on the disparity map which contains information of object detection and locations. The proposed work produces low errors (i.e., 12.11% and 14.01% nonocc and all errors) based on the KITTI dataset and capable to perform much better compared with before the proposed framework and competitive with some newly available methods.
Image segmentation by modified map ml estimationsijesajournal
Though numerous algorithms exist to perform image segmentation there are several issues
related to execution time of these algorithm. Image Segmentation is nothing but label relabeling
problem under probability framework. To estimate the label configuration, an iterative
optimization scheme is implemented to alternately carry out the maximum a posteriori (MAP)
estimation and the maximum likelihood (ML) estimations. In this paper this technique is
modified in such a way so that it performs segmentation within stipulated time period. The
extensive experiments shows that the results obtained are comparable with existing algorithms.
This algorithm performs faster execution than the existing algorithm to give automatic
segmentation without any human intervention. Its result match image edges very closer to
human perception.
Visual Cryptography using Image ThresholdingIRJET Journal
This document proposes a novel visual cryptography algorithm using image thresholding that generates shares of an image without requiring a key. The technique thresholds the secret image to create two shares such that individual shares do not reveal information about the secret image. The original image can be reconstructed by performing an OR operation on the pixel values of the shares using the threshold value, without any loss of quality or information. The algorithm was tested on color images in MATLAB and successfully recovered the original image from the shares.
Brain tumor segmentation using asymmetry based histogram thresholding and k m...eSAT Publishing House
This document presents a method for segmenting brain tumors from MRI images using asymmetry-based histogram thresholding and k-means clustering. The method involves 8 steps: 1) preprocessing the MRI image using sharpening and median filters, 2) computing histograms of the left and right halves of the image, 3) calculating a threshold value using the difference between left and right histograms, 4) applying thresholding and morphological operations to extract the tumor region, 5) applying k-means clustering and using the cluster centroids to refine the segmentation. The method is tested on 30 MRI images and results show the tumor region is accurately segmented. The segmented tumors can then be used for quantification, classification, and computer-assisted diagnosis of brain tumors.
IRJET- Saliency based Image Co-SegmentationIRJET Journal
The document describes a saliency-based image co-segmentation method. It proposes to first extract inter-image information through co-saliency maps generated from multiple saliency extraction methods. Then, it performs single image segmentation on each individual image. A key step is fusing the diverse saliency maps through a saliency co-fusion process at the superpixel level. This exploits inter-image information to boost common foreground regions and suppress background regions. Experiments show the co-fusion based approach achieves competitive performance compared to state-of-the-art methods without parameter tuning.
IRJET- Digital Image Forgery Detection using Local Binary Patterns (LBP) and ...IRJET Journal
This document proposes a method to detect digital image forgeries using local binary patterns (LBP) and histogram of oriented gradients (HOG). It extracts LBP features from the input image, then applies HOG to the LBP features. These combined features are classified using a support vector machine (SVM) as authentic or tampered. Testing on CASIA datasets achieved detection rates of 92.3% for CASIA-1 and 96.1% for CASIA-2, outperforming other existing methods. The method is effective at forgery detection while having reduced time complexity.
There exists a plethora of algorithms to perform image segmentation and there are several issues related to
execution time of these algorithms. Image Segmentation is nothing but label relabeling problem under
probability framework. To estimate the label configuration, an iterative optimization scheme is
implemented to alternately carry out the maximum a posteriori (MAP) estimation and the maximum
likelihood (ML) estimations. In this paper this technique is modified in such a way so that it performs
segmentation within stipulated time period. The extensive experiments shows that the results obtained are
comparable with existing algorithms. This algorithm performs faster execution than the existing algorithm
to give automatic segmentation without any human intervention. Its result match image edges very closer to
human perception.
This document compares image enhancement and analysis techniques using image processing and wavelet techniques on thermal images. It discusses various image enhancement methods such as converting images to grayscale, histogram equalization, contrast enhancement, linear and adaptive filtering, morphology, FFT transforms, and wavelet-based techniques including image fusion, denoising, and compression. Results showing enhanced, denoised, and compressed images are presented and analyzed. The document concludes that wavelet techniques provide better enhancement of thermal images compared to traditional image processing methods.
A DISCUSSION ON IMAGE ENHANCEMENT USING HISTOGRAM EQUALIZATION BY VARIOUS MET...pharmaindexing
This document summarizes several papers on image enhancement techniques using histogram equalization. It discusses papers that propose sub-region histogram equalization to improve contrast while preserving spatial relationships. It also discusses a 3D histogram equalization method that produces a uniform 1D grayscale histogram to overcome issues with previous color histogram methods. Another paper proposes using total variation minimization for cartoon-texture decomposition prior to histogram equalization to reduce intensity saturation effects. Further, a technique called gain controllable clipped histogram equalization is presented to enhance contrast while preserving original brightness. Finally, a method called bi-histogram equalization with neighborhood metrics is described which divides histograms to improve local contrast while maintaining brightness.
The Computation Complexity Reduction of 2-D Gaussian FilterIRJET Journal
This document discusses reducing the computational complexity of a 2D Gaussian filter for image smoothing. It begins with an abstract that notes 2D Gaussian filters are commonly used for image smoothing but require heavy computational resources. It then proposes using fixed-point arithmetic rather than floating point to implement the filter on an FPGA, which can increase efficiency and decrease area and complexity. The document is divided into sections that cover the theory behind image filtering, image smoothing and sharpening, quality metrics for evaluation, and an energy scalable Gaussian smoothing filter architecture. It concludes by discussing results and benefits of implementing the filter using fixed-point arithmetic on an FPGA.
IRJET- An Improvised Multi Focus Image Fusion Algorithm through QuadtreeIRJET Journal
The document proposes a new quadtree-based algorithm for multi-focus image fusion. The algorithm divides the input images into 4 equal blocks using a quadtree structure. It then further divides each block into smaller blocks and detects the focused regions in each block using a focus measure and weighted values. The small blocks are then fused using a modified Laplacian mechanism. The fused image is evaluated using SSIM and ESSIM values, which indicate the proposed algorithm performs better fusion than previous methods.
IRJET- A Plant Identification and Recommendation SystemIRJET Journal
This document describes a plant identification and recommendation system that uses image recognition techniques. The system takes an image of a leaf as input, preprocesses it by resizing, converting to grayscale, and extracting features. It then uses a convolutional neural network with the Inception-v3 model to identify the plant by comparing features to those in its database. Based on the identified plant, it recommends other plants that could grow in that location. The system is implemented as both a mobile app and web application to be accessible anywhere.
IRJET - Symmetric Image Registration based on Intensity and Spatial Informati...IRJET Journal
This document presents a proposed system for symmetric image registration based on intensity and spatial information using a technique called the Coloured Simple Algebraic Algorithm (CSAA). The system first preprocesses color images, extracts features, then classifies images as symmetric or asymmetric using a neural network. It is shown to provide accurate and robust registration of medical and biomedical images. The system is implemented and evaluated on sample images, demonstrating it can successfully identify symmetric versus asymmetric images. The proposed approach aims to improve on existing techniques for intensity-based image registration tasks.
Improved Performance of Fuzzy Logic Algorithm for Lane Detection ImagesIRJET Journal
1) The document proposes improving lane detection algorithms by modifying the Hough transform with fuzzy logic to handle curved lane images better.
2) It compares the performance of the traditional Hough transform method to the proposed fuzzy logic-based method using metrics like recall, accuracy, and error rates.
3) The results show that the proposed technique outperforms existing methods, particularly in the presence of noise, curved lanes, or other challenging image conditions.
Performance Evaluation of Lane Detection Images Based on Fuzzy LogicIRJET Journal
1. The document discusses lane detection techniques for autonomous vehicles using fuzzy logic. It aims to improve lane detection accuracy by modifying the Hough transform with fuzzy logic and different performance metrics.
2. The key techniques discussed are binarization, curve fitting, and the Hough transform. Binarization is used as a pre-processing step. Curve fitting is used to model the visual characteristics extracted from frames to represent the road. The Hough transform is commonly used for line detection but can fail on curved roads.
3. The authors propose using fuzzy logic with the Hough transform to improve lane detection on curved roads by integrating different performance metrics. They claim experimental results show the proposed technique outperforms existing methods.
Image Features Matching and Classification Using Machine LearningIRJET Journal
This document presents a research paper that proposes a new methodology for image feature matching and classification using machine learning. The paper aims to improve accuracy and robustness in feature extraction and matching between digital images. The proposed methodology extracts features from images using machine learning, matches common features between images, and classifies objects. It is evaluated based on precision, recall, and F1-score, and shows improved performance over traditional Scale Invariant Feature Transform (SIFT) techniques on tested datasets with different objects. The proposed approach extracts fewer features and takes less computation time than traditional methods.
IRJET - Face Recognition based Attendance SystemIRJET Journal
This document describes a face recognition-based attendance system. It begins with an introduction to face recognition and the challenges of implementing such a system in real-time. It then reviews related work on algorithms used for face detection (Haar cascade), feature extraction (Histogram of Oriented Gradients), and recognition (Convolutional Neural Networks). The proposed system is described as collecting a student database, extracting encodings from images using CNN, and comparing real-time detected faces to the database using HOG detection and Euclidean distance matching to mark attendance. Experimental results aimed to test recognition under different training, lighting, and pose conditions.
IRJET- Image based Approach for Indian Fake Note Detection by Dark Channe...IRJET Journal
This document presents a proposed method for detecting fake Indian currency notes using image processing techniques. The proposed system takes an image of a currency note as input and performs pre-processing including resizing, restoration, and enhancement. It then applies "X-ray vision" using dark channel prior to extract inner and outer edges of patterns in the image. The extracted patterns are labeled and classified using a fuzzy classifier. The system is able to classify images as real or fake currency with 90-95% accuracy. The document reviews related work on currency detection and provides details on the proposed methodology, which includes image acquisition, pre-processing, enhancement, dark channel prior, labeling, and fuzzy classification. Results are presented showing the output of each step.
IRJET- Analysis of Vehicle Number Plate RecognitionIRJET Journal
This document summarizes research on techniques for enhancing license plate images and improving vehicle number plate recognition. It discusses using forward motion deblurring, scale-based region growing, blur estimation, blind image deblurring, and a no-reference metric to enhance license plate image details and obtain deblurred images. The document also reviews related work applying these and other techniques, such as binary SIFT, energy cooperation in wireless networks, and parametric blur estimation for natural image restoration. The goal is to develop more accurate and robust methods for automatic license plate recognition.
IRJET-MText Extraction from Images using Convolutional Neural NetworkIRJET Journal
The document describes a text extraction model that uses convolutional neural networks (CNNs) to detect and recognize text in images. It discusses pre-processing techniques like binarization and filtering used to improve accuracy. A CNN based on ResNet18 architecture is used for text recognition, trained with CTC loss to handle variable-length text. Keywords can be searched for in extracted text and highlighted. The system allows browsing images, extracting text, searching text, and storing extracted text in an editable document format. While current technology can extract text from simple backgrounds, this model aims to handle more complex real-world images.
Face Recognition Technique using ICA and LBPHIRJET Journal
The document describes a face recognition technique that uses Independent Component Analysis (ICA) and Local Binary Pattern Histograms (LBPH). It begins with an introduction to face recognition and the challenges involved. Then it describes LBPH, which extracts local features from images by comparing pixel intensities to the center pixel. ICA is also introduced as a method for extracting independent components from images to better represent faces across changes. The proposed technique applies both ICA and LBPH to extract features, then uses those features for face recognition by comparing an unknown image to training images. It claims this approach provides good recognition performance across variations in poses, illumination and sizes.
Geo Spatial Data And it’s Quality AssessmentIRJET Journal
This document discusses assessing the quality of geospatial data generated from unmanned aerial vehicle (UAV) images. The study area was approximately 5-6 km of the Banaras Hindu University campus in Varanasi, India. Images were captured using a DJI Mavic Pro Platinum drone and processed using ArcGIS Pro and Pix4dmapper to generate orthophotos, point clouds, and 3D models. The horizontal and vertical accuracies of the UAV solution were analyzed. Statistical analysis, including a paired t-test, showed the differences between UAV-derived data and reference GPS points were within acceptable limits of accuracy. The analysis demonstrated that accurate geospatial data can be produced from UAV images.
IRJET- Fusion based Brain Tumor DetectionIRJET Journal
1. The document discusses a method for detecting brain tumors using medical image fusion and support vector machines (SVM).
2. It involves fusing two MRI images using SVM to create a single fused image with more information than the original images. Texture and wavelet features are then extracted from the fused image.
3. The SVM classifier classifies the brain tumors as benign or malignant based on the trained and tested features extracted from the fused image.
IRJET- Object Detection using Hausdorff DistanceIRJET Journal
This document proposes a new object recognition system using Hausdorff distance. The system aims to improve on existing methods like YOLO that struggle with small objects and can capture garbage data. The document outlines preprocessing steps like noise cancellation, representing shapes as point sets, and extracting features. It then describes using Hausdorff distance and shape context to find the best match between input and reference shapes. Testing on datasets showed encouraging results for recognizing handwritten digits.
IRJET- Image Segmentation Techniques: A ReviewIRJET Journal
1. The document discusses and reviews various techniques for image segmentation, including edge detection, threshold-based, region-based, and neural network-based methods.
2. Edge detection separates images by detecting changes in pixel intensity or color to find edges and boundaries. Threshold-based methods segment images based on pixel intensity levels compared to a threshold. Region-based methods partition images into homogeneous regions of connected pixels. Neural network-based methods can perform automated segmentation through supervised or unsupervised machine learning.
3. Prior research has evaluated these techniques, finding that edge detection works best with clear edges but struggles with noise or smooth boundaries, and thresholding methods can miss details but are simple to implement. Region-based and neural network
IRJET - Object Detection using Hausdorff DistanceIRJET Journal
This document proposes using Hausdorff distance for object detection as it can better handle noise compared to other methods like Euclidean distance. The document discusses preprocessing images using Gaussian filtering for noise cancellation. It then represents shapes as point sets for feature extraction before using Hausdorff distance to match shapes between reference and test images for object recognition. Encouraging results were obtained when testing on MNIST, COIL and private handwritten digit datasets.
Improving Graph Based Model for Content Based Image RetrievalIRJET Journal
This document summarizes a research paper that proposes improvements to a graph-based model called Manifold Ranking (MR) for content-based image retrieval. Specifically, it introduces a novel scalable graph-based ranking model called Efficient Manifold Ranking (EMR) that addresses shortcomings of MR in scalable graph construction and efficient ranking computation. The proposed EMR model builds an anchor graph on the database instead of a traditional k-nearest neighbor graph, and designs a new form of adjacency matrix to speed up the ranking computation. Experimental results on large image databases demonstrate that EMR is effective for real-world image retrieval applications.
IRJET - Finger Vein Extraction and Authentication System for ATMIRJET Journal
This document summarizes a research paper on a finger vein extraction and authentication system for ATMs. The system uses repeated line tracking during feature extraction to improve the analysis of 256 pixels in finger vein images. During preprocessing, images undergo binarization, edge detection to isolate the finger region of interest, and enhancement. Features are then extracted using the repeated line tracking before classification with support vector machines. The system was tested on images from 30 subjects and achieved a peak signal to noise ratio of 78.1443 for identification, demonstrating its potential for biometric authentication applications like ATMs.
IRJET- Automated Student’s Attendance Management using Convolutional Neural N...IRJET Journal
This document describes a proposed system to automate student attendance management using convolutional neural networks and face recognition. The system would take attendance automatically by detecting faces in the classroom and comparing them to a database of student faces. This would make the attendance process more efficient than current manual methods like calling roll numbers or paper sign-ins. The system would use a CNN algorithm and face detection/recognition techniques like PCA to detect and identify student faces during lectures and automatically update attendance records.
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TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
Cricket management system ptoject report.pdfKamal Acharya
The aim of this project is to provide the complete information of the National and
International statistics. The information is available country wise and player wise. By
entering the data of eachmatch, we can get all type of reports instantly, which will be
useful to call back history of each player. Also the team performance in each match can
be obtained. We can get a report on number of matches, wins and lost.
Sachpazis_Consolidation Settlement Calculation Program-The Python Code and th...Dr.Costas Sachpazis
Consolidation Settlement Calculation Program-The Python Code
By Professor Dr. Costas Sachpazis, Civil Engineer & Geologist
This program calculates the consolidation settlement for a foundation based on soil layer properties and foundation data. It allows users to input multiple soil layers and foundation characteristics to determine the total settlement.
This is an overview of my current metallic design and engineering knowledge base built up over my professional career and two MSc degrees : - MSc in Advanced Manufacturing Technology University of Portsmouth graduated 1st May 1998, and MSc in Aircraft Engineering Cranfield University graduated 8th June 2007.
Better Builder Magazine brings together premium product manufactures and leading builders to create better differentiated homes and buildings that use less energy, save water and reduce our impact on the environment. The magazine is published four times a year.
Sri Guru Hargobind Ji - Bandi Chor Guru.pdfBalvir Singh
Sri Guru Hargobind Ji (19 June 1595 - 3 March 1644) is revered as the Sixth Nanak.
• On 25 May 1606 Guru Arjan nominated his son Sri Hargobind Ji as his successor. Shortly
afterwards, Guru Arjan was arrested, tortured and killed by order of the Mogul Emperor
Jahangir.
• Guru Hargobind's succession ceremony took place on 24 June 1606. He was barely
eleven years old when he became 6th Guru.
• As ordered by Guru Arjan Dev Ji, he put on two swords, one indicated his spiritual
authority (PIRI) and the other, his temporal authority (MIRI). He thus for the first time
initiated military tradition in the Sikh faith to resist religious persecution, protect
people’s freedom and independence to practice religion by choice. He transformed
Sikhs to be Saints and Soldier.
• He had a long tenure as Guru, lasting 37 years, 9 months and 3 days