This document summarizes techniques for removing haze and other pollutants from images. It discusses using a dark channel prior method based on observations that at least one color channel has pixels with low values. Transmission maps and atmospheric light can be estimated using this dark channel prior. The document also discusses using depth estimation, wavelet-based techniques, enhancement-based techniques, filtering-based techniques, supervised learning-based techniques, fusion-based techniques, and meta-heuristic system-based techniques for haze removal. It provides an overview of these different haze removal techniques.
Multi Image Deblurring using Complementary Sets of Fluttering Patterns by Mul...IRJET Journal
This document discusses a proposed method for multi-image deblurring using complementary sets of fluttering patterns and an alternating direction multiplier method. Existing methods for coded exposure and multi-image deblurring have limitations like generating complex fluttering patterns, low signal-to-noise ratio, and loss of spectral information. The proposed method uses a multiplier algorithm to optimize a latent image and generate simple binary fluttering patterns for single or multiple input images. This helps reduce spectral loss and recover spatially consistent deblurred images with minimum noise. The method involves preprocessing the input image, setting regularization parameters, performing deconvolution iteratively using matrices, and outputting a deblurred image with sharp details and low noise.
This paper analyzed different haze removal methods. Haze causes trouble to
many computer graphics/vision applications as it reduces the visibility of the scene. Air light and
attenuation are two basic phenomena of haze. air light enhances the whiteness in scene and on
the other hand attenuation reduces the contrast. the colour and contrast of the scene is recovered
by haze removal techniques. many applications like object detection , surveillance, consumer
electronics etc. apply haze removal techniques. this paper widely focuses on the methods of
effectively eliminating haze from digital images. it also indicates the demerits of current
techniques.
Highly Adaptive Image Restoration In Compressive Sensing Applications Using S...IJARIDEA Journal
This document presents a method for highly adaptive image restoration in compressive sensing applications using sparse dictionary learning (SDL) technique. It begins with an introduction to image restoration and compressive sensing. Then it discusses related works including total variation minimization, cosine algorithm, discrete wavelet transform, and Metropolis-Hastings algorithm. The proposed scheme is described involving sparse dictionary learning, extracting patches from an image, matching patches to a dictionary, stacking similar patches, and reconstructing the image. Results show the SDL technique achieves higher PSNR values than other methods compared. In conclusion, images can be effectively restored with adaptive dictionary learning in compressive sensing, though it requires more computation time than other methods.
Survey on Image Integration of Misaligned ImagesIRJET Journal
The document discusses methods for integrating misaligned images to improve image quality under low lighting conditions. It reviews previous works that combine images like flash/no-flash pairs to transfer details and color, but have limitations when images are misaligned. The paper proposes a new method using a long-exposure image and flash image that introduces a local linear model to transfer color while maintaining natural colors and high contrast, without deteriorating contrast for misaligned pairs. It concludes that handling misaligned images remains a challenge with existing methods and further work is needed.
1. The document discusses techniques for removing haze from digital images. It begins with an introduction to how haze forms and degrades image quality.
2. It then describes several categories of haze removal techniques, including multiple image dehazing methods that use multiple images and single image dehazing methods that rely on statistical assumptions. Specific techniques discussed include dark channel prior, guided image filtering, and bilateral filtering.
3. The document focuses on comparing different haze removal approaches and evaluating which methods produce higher quality results for single image dehazing.
RADAR Images are strongly preferred for analysis of geospatial information about earth surface to assesse envirmental conditions radar images are captured by different remote sensors and that images are combined together to get complementary information. To collect radar images SAR(Synthetic Aperture Radar) sensors are used which are active sensors and can gather information during day and night without affecting weather conditions. We have discussed DCT and DWT image fusion methods,which gives us more informative fused image simultaneously we have checked performance parameters among these two methods to get superior method from these two techniques
Survey on Various Image Denoising TechniquesIRJET Journal
This document summarizes several techniques for image denoising. It begins by defining image noise and explaining how noise degrades image quality. It then reviews 7 different published techniques for image denoising, summarizing the key aspects of each technique. These include methods using local spectral component decomposition, SVD-based denoising, patch-based near-optimal denoising, LPG-PCA denoising, trivariate shrinkage filtering, SURE-LET denoising, and 3D transform-domain collaborative filtering. The document concludes that LSCD provides better denoising results according to PSNR analysis and provides an overview of the state-of-the-art in image denoising techniques.
International Journal of Engineering Research and DevelopmentIJERD Editor
This document summarizes a study on context-based image segmentation of radiography images to detect defects in welds. The researchers developed a simple image processing technique that uses contextual knowledge about radiography images rather than standard techniques. They first identify regions of interest using edge detection. They then segment potential flaws from the image using a statistical threshold based on the mean and standard deviation of pixel values in neighboring regions, rather than global thresholding. They show their technique successfully segments flaws like porosity and fine cracks from test images. Future work will involve extracting features of segmented flaws and using machine learning for classification.
Multi Image Deblurring using Complementary Sets of Fluttering Patterns by Mul...IRJET Journal
This document discusses a proposed method for multi-image deblurring using complementary sets of fluttering patterns and an alternating direction multiplier method. Existing methods for coded exposure and multi-image deblurring have limitations like generating complex fluttering patterns, low signal-to-noise ratio, and loss of spectral information. The proposed method uses a multiplier algorithm to optimize a latent image and generate simple binary fluttering patterns for single or multiple input images. This helps reduce spectral loss and recover spatially consistent deblurred images with minimum noise. The method involves preprocessing the input image, setting regularization parameters, performing deconvolution iteratively using matrices, and outputting a deblurred image with sharp details and low noise.
This paper analyzed different haze removal methods. Haze causes trouble to
many computer graphics/vision applications as it reduces the visibility of the scene. Air light and
attenuation are two basic phenomena of haze. air light enhances the whiteness in scene and on
the other hand attenuation reduces the contrast. the colour and contrast of the scene is recovered
by haze removal techniques. many applications like object detection , surveillance, consumer
electronics etc. apply haze removal techniques. this paper widely focuses on the methods of
effectively eliminating haze from digital images. it also indicates the demerits of current
techniques.
Highly Adaptive Image Restoration In Compressive Sensing Applications Using S...IJARIDEA Journal
This document presents a method for highly adaptive image restoration in compressive sensing applications using sparse dictionary learning (SDL) technique. It begins with an introduction to image restoration and compressive sensing. Then it discusses related works including total variation minimization, cosine algorithm, discrete wavelet transform, and Metropolis-Hastings algorithm. The proposed scheme is described involving sparse dictionary learning, extracting patches from an image, matching patches to a dictionary, stacking similar patches, and reconstructing the image. Results show the SDL technique achieves higher PSNR values than other methods compared. In conclusion, images can be effectively restored with adaptive dictionary learning in compressive sensing, though it requires more computation time than other methods.
Survey on Image Integration of Misaligned ImagesIRJET Journal
The document discusses methods for integrating misaligned images to improve image quality under low lighting conditions. It reviews previous works that combine images like flash/no-flash pairs to transfer details and color, but have limitations when images are misaligned. The paper proposes a new method using a long-exposure image and flash image that introduces a local linear model to transfer color while maintaining natural colors and high contrast, without deteriorating contrast for misaligned pairs. It concludes that handling misaligned images remains a challenge with existing methods and further work is needed.
1. The document discusses techniques for removing haze from digital images. It begins with an introduction to how haze forms and degrades image quality.
2. It then describes several categories of haze removal techniques, including multiple image dehazing methods that use multiple images and single image dehazing methods that rely on statistical assumptions. Specific techniques discussed include dark channel prior, guided image filtering, and bilateral filtering.
3. The document focuses on comparing different haze removal approaches and evaluating which methods produce higher quality results for single image dehazing.
RADAR Images are strongly preferred for analysis of geospatial information about earth surface to assesse envirmental conditions radar images are captured by different remote sensors and that images are combined together to get complementary information. To collect radar images SAR(Synthetic Aperture Radar) sensors are used which are active sensors and can gather information during day and night without affecting weather conditions. We have discussed DCT and DWT image fusion methods,which gives us more informative fused image simultaneously we have checked performance parameters among these two methods to get superior method from these two techniques
Survey on Various Image Denoising TechniquesIRJET Journal
This document summarizes several techniques for image denoising. It begins by defining image noise and explaining how noise degrades image quality. It then reviews 7 different published techniques for image denoising, summarizing the key aspects of each technique. These include methods using local spectral component decomposition, SVD-based denoising, patch-based near-optimal denoising, LPG-PCA denoising, trivariate shrinkage filtering, SURE-LET denoising, and 3D transform-domain collaborative filtering. The document concludes that LSCD provides better denoising results according to PSNR analysis and provides an overview of the state-of-the-art in image denoising techniques.
International Journal of Engineering Research and DevelopmentIJERD Editor
This document summarizes a study on context-based image segmentation of radiography images to detect defects in welds. The researchers developed a simple image processing technique that uses contextual knowledge about radiography images rather than standard techniques. They first identify regions of interest using edge detection. They then segment potential flaws from the image using a statistical threshold based on the mean and standard deviation of pixel values in neighboring regions, rather than global thresholding. They show their technique successfully segments flaws like porosity and fine cracks from test images. Future work will involve extracting features of segmented flaws and using machine learning for classification.
IJRET-V1I1P2 -A Survey Paper On Single Image and Video Dehazing MethodsISAR Publications
Most of the computer applications use digital images. Digital image processing acts an important
role in the analysis and interpretation of data, which is in the digital form. Images taken in foggy
weather condition often suffer from poor visibility and clarity. After the study of several fast
dehazing methods like Tan’s dehazing technique, Fattal’s dehazing technique and aiming Heat al
dehazing technique, Dark Channel Prior (DCP) intended by He et al is most substantive technique
for dehazing.This survey aims to study about various existing methods such as polarization, dark
channel prior, depth map based method etc. are used for dehazing.
IRJET - Underwater Image Enhancement using PCNN and NSCT FusionIRJET Journal
This document discusses techniques for enhancing underwater images that have been degraded due to scattering and absorption in the water medium. It proposes a new method for color image fusion using Non-Subsampled Contourlet Transform (NSCT) and Pulse Coupled Neural Network (PCNN). NSCT is used to decompose the image into sub-bands, while PCNN is used to fuse the high frequency sub-band coefficients. The proposed method is shown to outperform other fusion methods in objective quality assessment metrics. Various other underwater image enhancement techniques are also discussed, including wavelength compensation, multi-band fusion, image mode filtering, and approaches using neural networks like convolutional neural networks.
In general, analysing cameras is a difficult problem and solutions are often found only for geometric
approach. In this paper, the image capturing capability of a camera is presented from optical perspective.
Since most compact cameras can acquire only visible light, the description and propagation method of the
visible part of the electromagnetic spectrum reflected by a scene object is made based on Maxwell’s
equations. We then seek to use this understanding in the modelling of the image formation process of the
camera. The dependency of camera sensor field distribution on aperture dimension is emphasized. This
modelling leads to an important camera and image quality parameter called Modulation Transfer
Function. The model presented is based on a wave optics in which the wavefront is modified by the lens
after diffraction has taken place at the camera rectangular aperture positioned at the front focal point of
the lens. Simulation results are presented to validate the approach.
Wave Optics Analysis of Camera Image Formation With Respect to Rectangular Ap...IJCSEA Journal
In general, analysing cameras is a difficult problem and solutions are often found only for geometric approach. In this paper, the image capturing capability of a camera is presented from optical perspective. Since most compact cameras can acquire only visible light, the description and propagation method of the visible part of the electromagnetic spectrum reflected by a scene object is made based on Maxwell’s equations. We then seek to use this understanding in the modelling of the image formation process of the camera. The dependency of camera sensor field distribution on aperture dimension is emphasized. This modelling leads to an important camera and image quality parameter called Modulation Transfer Function. The model presented is based on a wave optics in which the wavefront is modified by the lens after diffraction has taken place at the camera rectangular aperture positioned at the front focal point of the lens. Simulation results are presented to validate the approach.
A fast single image haze removal algorithm using color attenuation priorLogicMindtech Nologies
IMAGE PROCESSING Projects for M. Tech, IMAGE PROCESSING Projects in Vijayanagar, IMAGE PROCESSING Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, IMAGE PROCESSING IEEE projects in Bangalore, IEEE 2015 IMAGE PROCESSING Projects, MATLAB Image Processing Projects, MATLAB Image Processing Projects in Bangalore, MATLAB Image Processing Projects in Vijayangar
Effective segmentation of sclera, iris and pupil in noisy eye imagesTELKOMNIKA JOURNAL
In today’s sensitive environment, for personal authentication, iris recognition is the most attentive
technique among the various biometric technologies. One of the key steps in the iris recognition system is
the accurate iris segmentation from its surrounding noises including pupil and sclera of a captured
eye-image. In our proposed method, initially input image is preprocessed by using bilateral filtering.
After the preprocessing of images contour based features such as, brightness, color and texture features
are extracted. Then entropy is measured based on the extracted contour based features to effectively
distinguishing the data in the images. Finally, the convolution neural network (CNN) is used for
the effective sclera, iris and pupil parts segmentations based on the entropy measure. The proposed
results are analyzed to demonstrate the better performance of the proposed segmentation method than
the existing methods.
Medical Images are regularly of low contrast and boisterous/Noisy (absence of clarity) because of
the circumstances they are being taken. De-noising these pictures is a troublesome undertaking as they
ought to exclude any antiquities or obscuring of edges in the pictures. The Bayesian shrinkage strategy has
been chosen for thresholding in light of its sub band reliance property. The spatial space and Wavelet
based de-noising systems utilizing delicate thresholding strategy are contrasted and the proposed technique
utilizing GA (Genetic Algorithm) is used. The GA procedure is proposed in view of PSNR and results are
contrasted and existing spatial space and wavelet based de-noising separating strategies. The proposed
calculation gives improved visual clarity to diagnosing the restorative pictures. The proposed strategy in
view of GA surveys the better execution on the premise of the quantitative metric i.e PSNR (Peak Signal
to Noise-Ratio) and visual impacts. Reenactment results demonstrate that the GA based proposed
technique beats the current de-noising separating strategies.
Despeckling of Sar Image using Curvelet TransformIRJET Journal
This document presents a method for reducing speckle noise in synthetic aperture radar (SAR) images using the curvelet transform. SAR images are affected by speckle noise during image capture and transmission. The curvelet transform is used to decompose the SAR image into different scales and orientations. Thresholding is applied to the curvelet coefficients to remove coefficients corresponding to noise. The inverse curvelet transform is then applied to reconstruct the denoised image. Experimental results on SAR images show that the proposed curvelet-based method achieves higher peak signal-to-noise ratio and lower mean squared error than conventional filters, indicating it more effectively removes noise while preserving image detail.
This document discusses atmospheric turbulence degraded image restoration using back propagation neural network. It proposes using a feed-forward neural network with 20 hidden layers and one output layer trained with backpropagation to restore images degraded by atmospheric turbulence and noise. The network is trained on normalized input images and tested on blurred images. Results show the proposed method achieves higher PSNR values than other techniques like kurtosis minimization and PCA, indicating better image quality restoration. Future work may incorporate median filtering and using first order image features for network weight assignment.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity
The document discusses superresolution technology that can improve the resolution of infrared camera images. It begins by explaining the basic problem that small objects may be invisible or measured incorrectly in infrared images due to pixel size limitations. It then describes how superresolution works by using multiple images and deconvolution algorithms to effectively decrease pixel pitch by 1.6x and increase usable resolution also by 1.6x compared to normal images. Experimental results show that superresolution detects spatial frequencies about 50% higher than the camera's detector cutoff and improves temperature measurement accuracy compared to interpolation. The technology will be available as a software update for all current Testo infrared cameras.
A Review over Different Blur Detection Techniques in Image Processingpaperpublications3
Abstract: In last few years there is lot of development and attentions in area of blur detection techniques. The Blur detection techniques are very helpful in real life application and are used in image segmentation, image restoration and image enhancement. Blur detection techniques are used to remove the blur from a blurred region of an image which is due to defocus of a camera or motion of an object. In this literature review we represent some techniques of blur detection such as Blind image de-convolution, Low depth of field, Edge sharpness analysis, and Low directional high frequency energy. After studying all these techniques we have found that there are lot of future work is required for the development of perfect and effective blur detection technique.
1. The document presents a method for super resolution of text images using ant colony optimization. It involves registering multiple low resolution images, fusing them, performing soft classification to assign pixel values to multiple classes, and using ant colony optimization for super resolution mapping to increase the resolution.
2. Key steps include SURF-based image registration, intensity-based and discrete wavelet transform fusion, decision tree-based soft classification, and ant colony optimization to assign pixel values based on pheromone updating to increase resolution.
3. Test cases on images with angular displacement, blurred text, etc. show that the method increases resolution successfully but can add some noise, though processing is faster than alternatives. Ant colony optimization
Image Denoising of various images Using Wavelet Transform and Thresholding Te...IRJET Journal
The document discusses image denoising using wavelet transforms and thresholding techniques. It first provides background on image denoising and wavelet transforms. It then reviews several existing studies that used wavelet transforms like Haar, db4, and sym4 along with thresholding to denoise images corrupted with Gaussian and salt-and-pepper noise. Next, it describes the proposed denoising algorithm which involves adding noise to test images, decomposing the noisy images using different wavelet transforms, applying thresholding, and calculating metrics like PSNR to evaluate performance. The algorithm aims to eliminate noise in the wavelet domain using soft and hard thresholding followed by reconstruction.
Deblurring Image and Removing Noise from Medical Images for Cancerous Disease...IRJET Journal
This document summarizes a research paper that uses a Wiener filter to deblur and remove noise from medical images for cancer detection. The paper introduces different types of image blurring and noise, as well as deblurring and noise removal techniques. It then describes experiments using a Wiener filter on blurred and noisy medical images. The Wiener filter is shown to effectively deblur images and remove noise, improving image quality as measured by metrics like PSNR, MSE, RMSE and SSIM. The findings suggest the Wiener filter is a powerful tool for processing medical images.
High Efficiency Haze Removal Using Contextual Regularization AlgorithmIRJET Journal
This document presents a new contextual regularization algorithm for high efficiency haze removal. It begins with an overview of existing haze removal techniques and their limitations, such as halo effects and reduced image quality. It then proposes a method that estimates airlight using multiple transmission maps and cross bilateral filtering to remove noise and enhance edges. This integrated approach yields faster execution speeds and superior recovery effects compared to existing filters. The key contribution is a new contextual regularization that allows incorporating a filter bank into dehazing images. Experimental results show the proposed method removes haze without changing the original scene or producing saturated images, while existing techniques can remove wanted image information or produce unnatural results.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IRJET- Enhanced Layer based Approach in Multi Focus Image Fusion SWT Algo...IRJET Journal
This paper proposes a new layer-based approach for multi-focus image fusion to address discrepancies between noisy and infrared images. The approach decomposes image pairs into base and detail layers. A local contrast-preserving method creates a new base layer for the infrared image with visual appearance similar to the denoised noisy image's base layer. Three types of detail layers are designed from the noisy and infrared images. An optimization framework estimates the noise-free detail layer using residual-based sparsity and patch redundancy priors. Experimental results show the approach overcomes discrepancy problems and provides high-quality fused images with low noise and sharp edges, outperforming conventional residual-based fusion in mitigating ringing artifacts.
The document proposes a new framework called structure-modulated sparse representation (SMSR) for single image super-resolution. Existing super-resolution methods increase artifacts and do not consider image structure. The proposed SMSR algorithm formulates an optimization problem using gradient priors and nonlocal sparsity to reconstruct high-resolution images. It exploits multi-scale similarity using multi-step magnification and ridge regression for initial estimation. The algorithm also incorporates gradient histogram preservation as a regularization term. Experimental results show the proposed method outperforms state-of-the-art methods in recovering fine structures and details from low-resolution images.
IRJET- Robust Edge Detection using Moore’s Algorithm with Median FilterIRJET Journal
The document proposes a robust edge detection method using Moore's algorithm with median filtering. It performs foreground detection on input images to segment the foreground from background. Moore's neighbor algorithm is then used to trace boundaries and detect edges. Median filtering is also applied to remove noise while preserving edges. The method is tested on BSD dataset images and evaluated based on metrics like PSNR, SNR, RMSE, etc. Results show the proposed method performs better edge detection compared to modified Moore's algorithm, Canny Moore, and Sobel Moore approaches.
A Novel Dehazing Method for Color Accuracy and Contrast Enhancement Method fo...IRJET Journal
The document proposes a novel dehazing method for color accuracy and a contrast enhancement method for low light intensity images. The dehazing method involves three steps: 1) Region division based on white balance segmentation, 2) Estimation of local atmospheric light in each region, and 3) An iterative dehazing algorithm to remove haze from each region. The contrast enhancement method inverts the input image, applies the dehazing algorithm, and then inverts the dehazed image to produce an enhanced output. Experimental results show the proposed methods can effectively enhance images taken with mobile devices or cameras without color distortion.
IRJET- A Review on Image Denoising & Dehazing Algorithm to Improve Dark Chann...IRJET Journal
This document summarizes a research paper that proposes a new approach to simultaneously dehaze and denoise images using an adaptive windows method and a new energy model. The proposed technique estimates a transmission map using the dark channel prior to reduce haze artifacts and improve estimation precision. A numerical algorithm based on Chambolle–Pock is designed to efficiently solve the new variation model and produce haze-free and noise-free images. Experimental results on real scenes demonstrate the effectiveness of the approach.
IJRET-V1I1P2 -A Survey Paper On Single Image and Video Dehazing MethodsISAR Publications
Most of the computer applications use digital images. Digital image processing acts an important
role in the analysis and interpretation of data, which is in the digital form. Images taken in foggy
weather condition often suffer from poor visibility and clarity. After the study of several fast
dehazing methods like Tan’s dehazing technique, Fattal’s dehazing technique and aiming Heat al
dehazing technique, Dark Channel Prior (DCP) intended by He et al is most substantive technique
for dehazing.This survey aims to study about various existing methods such as polarization, dark
channel prior, depth map based method etc. are used for dehazing.
IRJET - Underwater Image Enhancement using PCNN and NSCT FusionIRJET Journal
This document discusses techniques for enhancing underwater images that have been degraded due to scattering and absorption in the water medium. It proposes a new method for color image fusion using Non-Subsampled Contourlet Transform (NSCT) and Pulse Coupled Neural Network (PCNN). NSCT is used to decompose the image into sub-bands, while PCNN is used to fuse the high frequency sub-band coefficients. The proposed method is shown to outperform other fusion methods in objective quality assessment metrics. Various other underwater image enhancement techniques are also discussed, including wavelength compensation, multi-band fusion, image mode filtering, and approaches using neural networks like convolutional neural networks.
In general, analysing cameras is a difficult problem and solutions are often found only for geometric
approach. In this paper, the image capturing capability of a camera is presented from optical perspective.
Since most compact cameras can acquire only visible light, the description and propagation method of the
visible part of the electromagnetic spectrum reflected by a scene object is made based on Maxwell’s
equations. We then seek to use this understanding in the modelling of the image formation process of the
camera. The dependency of camera sensor field distribution on aperture dimension is emphasized. This
modelling leads to an important camera and image quality parameter called Modulation Transfer
Function. The model presented is based on a wave optics in which the wavefront is modified by the lens
after diffraction has taken place at the camera rectangular aperture positioned at the front focal point of
the lens. Simulation results are presented to validate the approach.
Wave Optics Analysis of Camera Image Formation With Respect to Rectangular Ap...IJCSEA Journal
In general, analysing cameras is a difficult problem and solutions are often found only for geometric approach. In this paper, the image capturing capability of a camera is presented from optical perspective. Since most compact cameras can acquire only visible light, the description and propagation method of the visible part of the electromagnetic spectrum reflected by a scene object is made based on Maxwell’s equations. We then seek to use this understanding in the modelling of the image formation process of the camera. The dependency of camera sensor field distribution on aperture dimension is emphasized. This modelling leads to an important camera and image quality parameter called Modulation Transfer Function. The model presented is based on a wave optics in which the wavefront is modified by the lens after diffraction has taken place at the camera rectangular aperture positioned at the front focal point of the lens. Simulation results are presented to validate the approach.
A fast single image haze removal algorithm using color attenuation priorLogicMindtech Nologies
IMAGE PROCESSING Projects for M. Tech, IMAGE PROCESSING Projects in Vijayanagar, IMAGE PROCESSING Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, IMAGE PROCESSING IEEE projects in Bangalore, IEEE 2015 IMAGE PROCESSING Projects, MATLAB Image Processing Projects, MATLAB Image Processing Projects in Bangalore, MATLAB Image Processing Projects in Vijayangar
Effective segmentation of sclera, iris and pupil in noisy eye imagesTELKOMNIKA JOURNAL
In today’s sensitive environment, for personal authentication, iris recognition is the most attentive
technique among the various biometric technologies. One of the key steps in the iris recognition system is
the accurate iris segmentation from its surrounding noises including pupil and sclera of a captured
eye-image. In our proposed method, initially input image is preprocessed by using bilateral filtering.
After the preprocessing of images contour based features such as, brightness, color and texture features
are extracted. Then entropy is measured based on the extracted contour based features to effectively
distinguishing the data in the images. Finally, the convolution neural network (CNN) is used for
the effective sclera, iris and pupil parts segmentations based on the entropy measure. The proposed
results are analyzed to demonstrate the better performance of the proposed segmentation method than
the existing methods.
Medical Images are regularly of low contrast and boisterous/Noisy (absence of clarity) because of
the circumstances they are being taken. De-noising these pictures is a troublesome undertaking as they
ought to exclude any antiquities or obscuring of edges in the pictures. The Bayesian shrinkage strategy has
been chosen for thresholding in light of its sub band reliance property. The spatial space and Wavelet
based de-noising systems utilizing delicate thresholding strategy are contrasted and the proposed technique
utilizing GA (Genetic Algorithm) is used. The GA procedure is proposed in view of PSNR and results are
contrasted and existing spatial space and wavelet based de-noising separating strategies. The proposed
calculation gives improved visual clarity to diagnosing the restorative pictures. The proposed strategy in
view of GA surveys the better execution on the premise of the quantitative metric i.e PSNR (Peak Signal
to Noise-Ratio) and visual impacts. Reenactment results demonstrate that the GA based proposed
technique beats the current de-noising separating strategies.
Despeckling of Sar Image using Curvelet TransformIRJET Journal
This document presents a method for reducing speckle noise in synthetic aperture radar (SAR) images using the curvelet transform. SAR images are affected by speckle noise during image capture and transmission. The curvelet transform is used to decompose the SAR image into different scales and orientations. Thresholding is applied to the curvelet coefficients to remove coefficients corresponding to noise. The inverse curvelet transform is then applied to reconstruct the denoised image. Experimental results on SAR images show that the proposed curvelet-based method achieves higher peak signal-to-noise ratio and lower mean squared error than conventional filters, indicating it more effectively removes noise while preserving image detail.
This document discusses atmospheric turbulence degraded image restoration using back propagation neural network. It proposes using a feed-forward neural network with 20 hidden layers and one output layer trained with backpropagation to restore images degraded by atmospheric turbulence and noise. The network is trained on normalized input images and tested on blurred images. Results show the proposed method achieves higher PSNR values than other techniques like kurtosis minimization and PCA, indicating better image quality restoration. Future work may incorporate median filtering and using first order image features for network weight assignment.
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity
The document discusses superresolution technology that can improve the resolution of infrared camera images. It begins by explaining the basic problem that small objects may be invisible or measured incorrectly in infrared images due to pixel size limitations. It then describes how superresolution works by using multiple images and deconvolution algorithms to effectively decrease pixel pitch by 1.6x and increase usable resolution also by 1.6x compared to normal images. Experimental results show that superresolution detects spatial frequencies about 50% higher than the camera's detector cutoff and improves temperature measurement accuracy compared to interpolation. The technology will be available as a software update for all current Testo infrared cameras.
A Review over Different Blur Detection Techniques in Image Processingpaperpublications3
Abstract: In last few years there is lot of development and attentions in area of blur detection techniques. The Blur detection techniques are very helpful in real life application and are used in image segmentation, image restoration and image enhancement. Blur detection techniques are used to remove the blur from a blurred region of an image which is due to defocus of a camera or motion of an object. In this literature review we represent some techniques of blur detection such as Blind image de-convolution, Low depth of field, Edge sharpness analysis, and Low directional high frequency energy. After studying all these techniques we have found that there are lot of future work is required for the development of perfect and effective blur detection technique.
1. The document presents a method for super resolution of text images using ant colony optimization. It involves registering multiple low resolution images, fusing them, performing soft classification to assign pixel values to multiple classes, and using ant colony optimization for super resolution mapping to increase the resolution.
2. Key steps include SURF-based image registration, intensity-based and discrete wavelet transform fusion, decision tree-based soft classification, and ant colony optimization to assign pixel values based on pheromone updating to increase resolution.
3. Test cases on images with angular displacement, blurred text, etc. show that the method increases resolution successfully but can add some noise, though processing is faster than alternatives. Ant colony optimization
Image Denoising of various images Using Wavelet Transform and Thresholding Te...IRJET Journal
The document discusses image denoising using wavelet transforms and thresholding techniques. It first provides background on image denoising and wavelet transforms. It then reviews several existing studies that used wavelet transforms like Haar, db4, and sym4 along with thresholding to denoise images corrupted with Gaussian and salt-and-pepper noise. Next, it describes the proposed denoising algorithm which involves adding noise to test images, decomposing the noisy images using different wavelet transforms, applying thresholding, and calculating metrics like PSNR to evaluate performance. The algorithm aims to eliminate noise in the wavelet domain using soft and hard thresholding followed by reconstruction.
Deblurring Image and Removing Noise from Medical Images for Cancerous Disease...IRJET Journal
This document summarizes a research paper that uses a Wiener filter to deblur and remove noise from medical images for cancer detection. The paper introduces different types of image blurring and noise, as well as deblurring and noise removal techniques. It then describes experiments using a Wiener filter on blurred and noisy medical images. The Wiener filter is shown to effectively deblur images and remove noise, improving image quality as measured by metrics like PSNR, MSE, RMSE and SSIM. The findings suggest the Wiener filter is a powerful tool for processing medical images.
High Efficiency Haze Removal Using Contextual Regularization AlgorithmIRJET Journal
This document presents a new contextual regularization algorithm for high efficiency haze removal. It begins with an overview of existing haze removal techniques and their limitations, such as halo effects and reduced image quality. It then proposes a method that estimates airlight using multiple transmission maps and cross bilateral filtering to remove noise and enhance edges. This integrated approach yields faster execution speeds and superior recovery effects compared to existing filters. The key contribution is a new contextual regularization that allows incorporating a filter bank into dehazing images. Experimental results show the proposed method removes haze without changing the original scene or producing saturated images, while existing techniques can remove wanted image information or produce unnatural results.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IRJET- Enhanced Layer based Approach in Multi Focus Image Fusion SWT Algo...IRJET Journal
This paper proposes a new layer-based approach for multi-focus image fusion to address discrepancies between noisy and infrared images. The approach decomposes image pairs into base and detail layers. A local contrast-preserving method creates a new base layer for the infrared image with visual appearance similar to the denoised noisy image's base layer. Three types of detail layers are designed from the noisy and infrared images. An optimization framework estimates the noise-free detail layer using residual-based sparsity and patch redundancy priors. Experimental results show the approach overcomes discrepancy problems and provides high-quality fused images with low noise and sharp edges, outperforming conventional residual-based fusion in mitigating ringing artifacts.
The document proposes a new framework called structure-modulated sparse representation (SMSR) for single image super-resolution. Existing super-resolution methods increase artifacts and do not consider image structure. The proposed SMSR algorithm formulates an optimization problem using gradient priors and nonlocal sparsity to reconstruct high-resolution images. It exploits multi-scale similarity using multi-step magnification and ridge regression for initial estimation. The algorithm also incorporates gradient histogram preservation as a regularization term. Experimental results show the proposed method outperforms state-of-the-art methods in recovering fine structures and details from low-resolution images.
IRJET- Robust Edge Detection using Moore’s Algorithm with Median FilterIRJET Journal
The document proposes a robust edge detection method using Moore's algorithm with median filtering. It performs foreground detection on input images to segment the foreground from background. Moore's neighbor algorithm is then used to trace boundaries and detect edges. Median filtering is also applied to remove noise while preserving edges. The method is tested on BSD dataset images and evaluated based on metrics like PSNR, SNR, RMSE, etc. Results show the proposed method performs better edge detection compared to modified Moore's algorithm, Canny Moore, and Sobel Moore approaches.
A Novel Dehazing Method for Color Accuracy and Contrast Enhancement Method fo...IRJET Journal
The document proposes a novel dehazing method for color accuracy and a contrast enhancement method for low light intensity images. The dehazing method involves three steps: 1) Region division based on white balance segmentation, 2) Estimation of local atmospheric light in each region, and 3) An iterative dehazing algorithm to remove haze from each region. The contrast enhancement method inverts the input image, applies the dehazing algorithm, and then inverts the dehazed image to produce an enhanced output. Experimental results show the proposed methods can effectively enhance images taken with mobile devices or cameras without color distortion.
IRJET- A Review on Image Denoising & Dehazing Algorithm to Improve Dark Chann...IRJET Journal
This document summarizes a research paper that proposes a new approach to simultaneously dehaze and denoise images using an adaptive windows method and a new energy model. The proposed technique estimates a transmission map using the dark channel prior to reduce haze artifacts and improve estimation precision. A numerical algorithm based on Chambolle–Pock is designed to efficiently solve the new variation model and produce haze-free and noise-free images. Experimental results on real scenes demonstrate the effectiveness of the approach.
An Enhanced Adaptive Wavelet Transform Image Inpainting TechniqueIRJET Journal
The document discusses an enhanced adaptive wavelet transform image inpainting technique. It begins with an abstract that describes image inpainting as recovering missing regions of an image through various techniques. It then provides background on image inpainting, including different categories and applications. The proposed approach uses wavelet transform methods to restore complex image structures with large curvature. Evaluation is based on patch size and peak signal-to-noise ratio (PSNR) value.
IRJET- Image De-Blurring using Blind De-Convolution AlgorithmIRJET Journal
The document describes a study on blind image deblurring using a blind deconvolution algorithm. It discusses how blurring occurs in images and various techniques used for image restoration. The proposed method uses a blind deconvolution technique to restore an original sharp image from a blurred input image without prior knowledge of the point spread function. It adds blur to test images using Gaussian, motion and average blur models. The algorithm then applies maximum likelihood estimation and blind deconvolution to restore the blurred image. Experimental results show that the blind deconvolution method can deblur images faster than conventional approaches.
IRJET - Dehazing of Single Nighttime Haze Image using Superpixel MethodIRJET Journal
This document presents a new super-pixel based algorithm for removing haze from single nighttime images. It first decomposes the input hazy nighttime image into a glow image and glow-free hazy image using their relative smoothness. It then uses super-pixel segmentation to compute the atmospheric light and dark channel values for each pixel in the glow-free image. The transmission map is estimated from the dark channel using a weighted guided image filter. Compared to patch-based methods, using super-pixels can reduce morphological artifacts and allow a smaller filter radius to better preserve details. The proposed method is tested on nighttime hazy images and is able to effectively remove haze and restore clear nighttime scenes in 3 sentences or less
IRJET - Contrast and Color Improvement based Haze Removal of Underwater Image...IRJET Journal
This document proposes a method for removing haze from underwater images using fusion techniques. It involves three main steps:
1. Removal of haze from the input underwater image using a water shield filter to extract a dehazed image.
2. Denoising the dehazed image using a sequential algorithm to compensate for uneven lighting and enhance image features.
3. Fusing the dehazed and denoised images to produce a clear output image with both haze and noise removed.
The method aims to improve underwater image visibility and contrast correction in a simple and effective manner. Evaluation on sample images demonstrates reduced haze and artifacts after processing.
A Review on Airlight Estimation Haze Removal AlgorithmsIRJET Journal
This document reviews algorithms for estimating airlight to remove haze from images. It discusses how haze degrades image quality by attenuating light reflected from objects and adding atmospheric light. Common haze removal techniques rely on a atmospheric scattering model. The dark channel prior method estimates atmospheric light using the fact that at least one color channel will have some pixels with very low intensities in haze-free images. Bilateral, trilateral, and CLAHE filters can then be used as post-processing steps to improve results. The document aims to develop new airlight estimation methods with lower computational complexity.
IRJET- Matlab based Multi Feature Extraction in Image and Video Analysis ...IRJET Journal
This document discusses using MATLAB for multi-feature extraction in image and video analysis. It focuses on four techniques: 1) Improving image and video quality using histogram equalization, 2) Changing image and video formats, 3) Resizing images and videos, and 4) Compressing images and videos using wavelet compression techniques. It proposes combining these four techniques into one MATLAB-based software program to simplify image and video processing for users. The document reviews existing related work on individual techniques and argues the proposed approach integrates multiple techniques into a single tool.
Visibility Enhancement of Hazy Images using Depth Estimation ConceptIRJET Journal
This document presents a methodology to improve the visibility of hazy images using depth estimation. The proposed method first converts the input hazy image into white balance and contrast enhanced images. Depth estimation is then performed on these images to estimate the unknown depth from the camera to objects in the scene. Weight maps are generated from the white balance and contrast images and applied to Gaussian and Laplacian pyramids to estimate depth. A gamma correction is applied to the depth estimated image to further improve visibility. Experimental results show that the gamma corrected image has better visibility and a higher PSNR than the depth estimated image alone.
IRJET- A Comparative Analysis of various Visibility Enhancement Techniques th...IRJET Journal
This document provides a summary and analysis of various single image defogging techniques. It begins with an abstract that outlines how different fog removal algorithms detect and remove fog to improve image visibility. It then reviews several fog removal techniques from research papers. These include using fog density perception to estimate transmission maps, enhancing contrast using dark channel priors, combining dark channel priors with fuzzy logic for efficiency, using dark channel priors and guided filters to extract transmission maps and enhance images. The document aims to analyze and compare different techniques for efficiently removing fog from digital images.
X-Ray Image Enhancement using CLAHE MethodIRJET Journal
This document presents a method for enhancing X-ray images using Contrast Limited Adaptive Histogram Equalization (CLAHE). CLAHE improves local contrast and edge definition by applying histogram equalization separately to small regions of the image rather than the entire image. It prevents overamplification of noise that can occur with adaptive histogram equalization. The proposed method uses an image processing filter chain including noise reduction, high pass filtering, and CLAHE to enhance 2D X-ray images. Key parameters of the filter chain are optimized using an interior point algorithm. The goal is to provide customized tissue contrast for each treatment location to allow for accurate patient setup and analysis in radiation therapy. The CLAHE method is shown to effectively enhance contrast in X-
IRJET- Road Feature Extraction from High Resolution Satellite Images using Ne...IRJET Journal
This document describes a method to detect road damage like potholes using images from satellite or other platforms. It involves:
1. Acquiring high resolution images of roads from satellites or other sources.
2. Pre-processing the images by converting to grayscale and enhancing to remove noise.
3. Using a convolutional neural network (CNN) to extract features from the images by applying filters and pooling layers to detect patterns like potholes.
4. Classifying sections of the road as containing damage or not and notifying authorities automatically through an Android app if damage is found.
The goal is to accurately detect road damage from images to help authorities maintain roads and reduce accidents. The described method uses
ANALYSIS OF LUNG NODULE DETECTION AND STAGE CLASSIFICATION USING FASTER RCNN ...IRJET Journal
This document presents a method for detecting and classifying lung nodules using Faster R-CNN technique. It first segments the lung from CT images and extracts features using Dual-Tree Complex Wavelet Transform. A Back Propagation Neural Network is then used to classify patterns of interstitial lung diseases detected in the images. Fuzzy clustering is also proposed to segment abnormal regions of the lung. The method aims to help identify and diagnose common lung diseases like pleural effusion and interstitial lung disease in an automated manner from CT images.
This document discusses the applicability of image processing for evaluating surface roughness. It examines how several parameters can affect the accuracy and reliability of results, including the camera's pixel resolution, height and angle relative to the surface, lighting intensity, shutter speed, and image capture conditions. The study found that variation in results reached 33% when parameters changed. It recommends carefully controlling parameters like ensuring normal camera angle and adequate, consistent lighting. An artificial neural network analysis correlated parameters to grayscale values with 92.8% accuracy. The document concludes that multiple factors must be considered for image processing to accurately assess surface roughness.
This document summarizes and compares four no-reference blur estimation methods: (1) a scale adaptive wavelet transform method, (2) a method using energy of quadrature filters, (3) a kurtosis measurement method using discrete dyadic wavelet transform, and (4) a method measuring average edge width. The methods are evaluated on blurred, noisy, and compressed images from a database. Results show the quadrature filter method performs best except for compressed images, where a perceptual method works best. The scale adaptive and kurtosis methods degrade more with noise while the quadrature filter method is more robust.
A survey on efficient no reference blur estimation methodseSAT Journals
Abstract Blur estimation in image processing has come to be of great importance in assessing the quality of images. This work presents a survey of no-reference blur estimation methods. A no-reference method is particularly useful, when the input image used for blur estimation does not have an available corresponding reference image. This paper provides a comparison of the methodologies of four no-reference blur estimation methods. The first method applies a scale adaptive technique of blur estimation to get better accuracy in the results. The second blur metric involves finding the energy using second order derivatives of an image using derivative pair of quadrature filters. The third blur metric is based on the kurtosis measurement in the discrete dyadic wavelet transform (DDWT) of the images. The fourth method of blur estimation is obtained by finding the ratio of sum of the edge widths of all the detected edges to the total number of edges. The results provided are useful in comparing the methods based on metrics like Spearman correlation coefficient. The results are obtained by evaluation on images from the Laboratory for Image and Video Engineering (LIVE) database. The various methods are evaluated on the images by adding varying content of noise. The performance is evaluated for 3 different categories namely Gaussian blur, motion blur and also JPEG2000 compressed images. Blur estimation finds its application in quality assessment, image fusion and auto-focusing in images. The sharpness of an image can also be found from the blur metric as sharpness is inversely proportional to blur. Sharpness metrics can also be combined with other metrics to measure overall quality of the image. Keywords: Blur estimation, blur, no-reference
IRJET- Automated Detection of Diabetic Retinopathy using Compressed SensingIRJET Journal
This document describes a proposed method for automated detection of diabetic retinopathy using compressed sensing. It begins with an abstract that outlines the goal of identifying retinal diseases like diabetic retinopathy using image processing techniques. It then provides details on the proposed method, which involves preprocessing retinal images through steps like color conversion, filtering, and morphological operations. Features are then extracted using compressed sensing before classification of diabetic retinopathy. The method aims to allow early detection of retinal diseases to minimize vision damage.
IRJET- Improving Interpretability of an Underwater using Undecimated Wavelet ...IRJET Journal
This document presents a method for improving the interpretability of underwater images using undecimated wavelet transform. It involves several steps: (1) performing histogram equalization on the underwater image to improve contrast, (2) using white balancing to enhance dark regions, and (3) fusing the outputs of steps 1 and 2 using undecimated wavelet transform. Undecimated wavelet transform is a type of stationary wavelet transform that avoids downsampling, improving shift invariance over discrete wavelet transform. The proposed method is compared to existing wavelength decomposition and image dehazing algorithms. Initial results show improvements in color correction and contrast after applying white balancing, histogram equalization, and image fusion with undecimated wavelet transform
IRJET - A Systematic Observation in Digital Image Forgery Detection using MATLABIRJET Journal
This document summarizes a research paper that proposes a new method for detecting digital image forgeries using analysis of illumination inconsistencies. The method extracts texture and edge-based features from illuminant maps of face regions in an image. These features are then classified using machine learning to detect if faces are illuminated inconsistently, indicating tampering. The approach requires only minimal user interaction by specifying bounding boxes around faces. Evaluation shows the method achieves a 86% detection rate of spliced images, outperforming existing illumination-based approaches. The work presents an important step in reducing human interaction for illumination-based forgery detection.
This document summarizes a research paper that proposes a deep learning approach for low-light image and video enhancement. It presents a multi-branch low-light image enhancement network (MBLLEN) that extracts features at different levels and applies enhancement through multiple subnets. The outputs are then fused to construct the final enhanced image. The approach divides the enhancement task into sub-problems to handle brightness, contrast, artifacts, and noise concurrently. It outperforms existing methods on metrics like PSNR and SSIM and has better inter-frame consistency for videos. The technique can improve low-light image and video quality for applications like surveillance and computer vision.
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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
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A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
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Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
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Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
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A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
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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
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Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
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Review on studies and research on widening of existing concrete bridgesIRJET Journal
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React based fullstack edtech web applicationIRJET Journal
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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
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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.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
VARIABLE FREQUENCY DRIVE. VFDs are widely used in industrial applications for...PIMR BHOPAL
Variable frequency drive .A Variable Frequency Drive (VFD) is an electronic device used to control the speed and torque of an electric motor by varying the frequency and voltage of its power supply. VFDs are widely used in industrial applications for motor control, providing significant energy savings and precise motor operation.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELijaia
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Prediction of Electrical Energy Efficiency Using Information on Consumer's Ac...PriyankaKilaniya
Energy efficiency has been important since the latter part of the last century. The main object of this survey is to determine the energy efficiency knowledge among consumers. Two separate districts in Bangladesh are selected to conduct the survey on households and showrooms about the energy and seller also. The survey uses the data to find some regression equations from which it is easy to predict energy efficiency knowledge. The data is analyzed and calculated based on five important criteria. The initial target was to find some factors that help predict a person's energy efficiency knowledge. From the survey, it is found that the energy efficiency awareness among the people of our country is very low. Relationships between household energy use behaviors are estimated using a unique dataset of about 40 households and 20 showrooms in Bangladesh's Chapainawabganj and Bagerhat districts. Knowledge of energy consumption and energy efficiency technology options is found to be associated with household use of energy conservation practices. Household characteristics also influence household energy use behavior. Younger household cohorts are more likely to adopt energy-efficient technologies and energy conservation practices and place primary importance on energy saving for environmental reasons. Education also influences attitudes toward energy conservation in Bangladesh. Low-education households indicate they primarily save electricity for the environment while high-education households indicate they are motivated by environmental concerns.
Digital Twins Computer Networking Paper Presentation.pptxaryanpankaj78
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
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