International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
AN OPTIMAL SOLUTION FOR IMAGE EDGE DETECTION PROBLEM USING SIMPLIFIED GABOR W...IJCSEIT Journal
Edge detection plays a vital role in computer vision and image processing. Edge of the image is one of the
most significant features which are mainly used for image analyzing process. An efficient algorithm for
extracting the edge features of images using simplified version of Gabor Wavelet is proposed in this paper.
Conventional Gabor Wavelet is widely used for edge detection applications. Due do the high computational
complexity of conventional Gabor Wavelet, this may not be used for real time application. Simplified Gabor
wavelet based approach is highly effective at detecting both the location and orientation of edges. The
results proved that the performance of proposed Simplified version of Gabor wavelet is superior to
conventional Gabor Wavelet, other edge detection algorithm and other wavelet based approach. The
performance of the proposed method is proved with the help of FOM, PSNR and Average run time.
Abstract Edge detection is a fundamental tool used in most image processing applications. We proposed a simple, fast and efficient technique to detect the edge for the identifying, locating sharp discontinuities in an image and boundary of an image. In this paper, we found that proposed method called LookUp Table performs well, which requires least computational time as compared to conventional Edge Detection techniques. And also in this paper we presented a comparative performance of various conventional Edge Detection Techniques. Keywords: Edge detectors, Lookup table.
Enhanced Optimization of Edge Detection for High Resolution Images Using Veri...ijcisjournal
dge Detection plays a crucial role in Image Processing and Segmentation where a set of algorithms aims
to identify various portions of a digital image at which a sharpened image is observed in the output or
more formally has discontinuities. The contour of Edge Detection also helps in Object Detection and
Recognition. Image edges can be detected by using two attributes such as Gradient and Laplacian. In our
Paper, we proposed a system which utilizes Canny and Sobel Operators for Edge Detection which is a
Gradient First order derivative function for edge detection by using Verilog Hardware Description
Language and in turn compared with the results of the previous paper in Matlab. The process of edge
detection in Verilog significantly reduces the processing time and filters out unneeded information, while
preserving the important structural properties of an image. This edge detection can be used to detect
vehicles in Traffic Jam, Medical imaging system for analysing MRI, x-rays by using Xilinx ISE Design
Suite 14.2.
Land Boundary Detection of an Island using improved Morphological OperationCSCJournals
Image analysis is one of the important tasks to obtain the information about earth surface. To detect and mark a particular land area, it is required to have the image from remote place. To recognize the same, the accurate boundary of that area has to be detected. In this paper, the example of remote sensing image has been considered. The accurate detection of the boundary is a complex task. A novel method has been proposed in this paper to detect the boundary of such land. Mathematical morphology is a simple and efficient method for this type of task. The morphological analysis is performed using structure elements (SE). By using mathematical morphology the images can be enhanced and then the boundary can be detected easily. Simultaneously the noise is removed by using the proposed model. The results exhibit the performance of the proposed method. Keywords: Remote Sensing images ; Edge detection; Gray- scale Morphological analysis, Structuring Element (SE).
WAVELET PACKET BASED IRIS TEXTURE ANALYSIS FOR PERSON AUTHENTICATIONsipij
There is considerable rise in the research of iris recognition system over a period of time. Most of the
researchers has been focused on the development of new iris pre-processing and recognition algorithms for
good quail iris images. In this paper, iris recognition system using Haar wavelet packet is presented.
Wavelet Packet Transform (WPT ) which is extension of discrete wavelet transform has multi-resolution
approach. In this iris information is encoded based on energy of wavelet packets.. Our proposed work
significantly decreases the error rate in recognition of noisy images. A comparison of this work with nonorthogonal Gabor wavelets method is done. Computational complexity of our work is also less as
compared to Gabor wavelets method.
This paper represents a survey of various methods of video surveillance system which improves the security. The aim of this paper is to review of various moving object detection technics. This paper focuses on detection of moving objects in video surveillance system. Moving body detection is first important task for any video surveillance system. Detection of moving object is a challenging task. Tracking is required in higher level applications that require the location and shape of object in every frame. In this survey,paper described about optical flow method, Background subtraction, frame differencing to detect moving object. It also described tracking method based on Morphology technique.
Keywords -- Frame separation, Pre-processing, Object detection using frame difference, Optical flow,
Temporal Differencing and background subtraction. Object tracking
AN OPTIMAL SOLUTION FOR IMAGE EDGE DETECTION PROBLEM USING SIMPLIFIED GABOR W...IJCSEIT Journal
Edge detection plays a vital role in computer vision and image processing. Edge of the image is one of the
most significant features which are mainly used for image analyzing process. An efficient algorithm for
extracting the edge features of images using simplified version of Gabor Wavelet is proposed in this paper.
Conventional Gabor Wavelet is widely used for edge detection applications. Due do the high computational
complexity of conventional Gabor Wavelet, this may not be used for real time application. Simplified Gabor
wavelet based approach is highly effective at detecting both the location and orientation of edges. The
results proved that the performance of proposed Simplified version of Gabor wavelet is superior to
conventional Gabor Wavelet, other edge detection algorithm and other wavelet based approach. The
performance of the proposed method is proved with the help of FOM, PSNR and Average run time.
Abstract Edge detection is a fundamental tool used in most image processing applications. We proposed a simple, fast and efficient technique to detect the edge for the identifying, locating sharp discontinuities in an image and boundary of an image. In this paper, we found that proposed method called LookUp Table performs well, which requires least computational time as compared to conventional Edge Detection techniques. And also in this paper we presented a comparative performance of various conventional Edge Detection Techniques. Keywords: Edge detectors, Lookup table.
Enhanced Optimization of Edge Detection for High Resolution Images Using Veri...ijcisjournal
dge Detection plays a crucial role in Image Processing and Segmentation where a set of algorithms aims
to identify various portions of a digital image at which a sharpened image is observed in the output or
more formally has discontinuities. The contour of Edge Detection also helps in Object Detection and
Recognition. Image edges can be detected by using two attributes such as Gradient and Laplacian. In our
Paper, we proposed a system which utilizes Canny and Sobel Operators for Edge Detection which is a
Gradient First order derivative function for edge detection by using Verilog Hardware Description
Language and in turn compared with the results of the previous paper in Matlab. The process of edge
detection in Verilog significantly reduces the processing time and filters out unneeded information, while
preserving the important structural properties of an image. This edge detection can be used to detect
vehicles in Traffic Jam, Medical imaging system for analysing MRI, x-rays by using Xilinx ISE Design
Suite 14.2.
Land Boundary Detection of an Island using improved Morphological OperationCSCJournals
Image analysis is one of the important tasks to obtain the information about earth surface. To detect and mark a particular land area, it is required to have the image from remote place. To recognize the same, the accurate boundary of that area has to be detected. In this paper, the example of remote sensing image has been considered. The accurate detection of the boundary is a complex task. A novel method has been proposed in this paper to detect the boundary of such land. Mathematical morphology is a simple and efficient method for this type of task. The morphological analysis is performed using structure elements (SE). By using mathematical morphology the images can be enhanced and then the boundary can be detected easily. Simultaneously the noise is removed by using the proposed model. The results exhibit the performance of the proposed method. Keywords: Remote Sensing images ; Edge detection; Gray- scale Morphological analysis, Structuring Element (SE).
WAVELET PACKET BASED IRIS TEXTURE ANALYSIS FOR PERSON AUTHENTICATIONsipij
There is considerable rise in the research of iris recognition system over a period of time. Most of the
researchers has been focused on the development of new iris pre-processing and recognition algorithms for
good quail iris images. In this paper, iris recognition system using Haar wavelet packet is presented.
Wavelet Packet Transform (WPT ) which is extension of discrete wavelet transform has multi-resolution
approach. In this iris information is encoded based on energy of wavelet packets.. Our proposed work
significantly decreases the error rate in recognition of noisy images. A comparison of this work with nonorthogonal Gabor wavelets method is done. Computational complexity of our work is also less as
compared to Gabor wavelets method.
This paper represents a survey of various methods of video surveillance system which improves the security. The aim of this paper is to review of various moving object detection technics. This paper focuses on detection of moving objects in video surveillance system. Moving body detection is first important task for any video surveillance system. Detection of moving object is a challenging task. Tracking is required in higher level applications that require the location and shape of object in every frame. In this survey,paper described about optical flow method, Background subtraction, frame differencing to detect moving object. It also described tracking method based on Morphology technique.
Keywords -- Frame separation, Pre-processing, Object detection using frame difference, Optical flow,
Temporal Differencing and background subtraction. Object tracking
Computationally Efficient Methods for Sonar Image Denoising using Fractional ...CSCJournals
Sonar images produced due to the coherent nature of scattering phenomenon inherit a multiplicative component called speckle and contain almost homogeneous as well as textured regions with relatively rare edges. Speckle removal is a pre-processing step required in applications like the detection and classification of objects in the sonar image. In this paper computationally efficient Fractional Integral Mask algorithms to remove the speckle noise from sonar images is proposed. Riemann- Liouville definition of fractional calculus is used to create Fractional integral masks in eight directions. The use of a mask incorporated with the significant coefficients from the eight directional masks and a single convolution operation required in such case helps in obtaining the computational efficiency. The sonar image heterogeneous patch classification is based on a new proposed naive homogeneity index which depends on the texture strength of the patches and despeckling filters can be adjusted to these patches. The application of the mask convolution only to the selected patches again reduce the computational complexity. The non-homomorphic approach used in the proposed method avoids the undesired bias occurring in the traditional homomorphic approach. Experiments show that the mask size required directly depends on the fractional order. Mask size can be reduced for lower fractional orders thus ensuring the computation complexity reduction for lower orders. Experimental results substantiate the effectiveness of the despeckling method. The different non reference image performance evaluation criterion are used to evaluate the proposed method.
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.
AN ENHANCED BLOCK BASED EDGE DETECTION TECHNIQUE USING HYSTERESIS THRESHOLDING sipij
Edge detection is a crucial step in various image processing systems like computer vision , pattern
recognition and feature extraction. The Canny edge detection algorithm even though exhibits high
accuracy, is computationally more complex compared to other edge detection techniques. A block based
distributed edge detection technique is presented in this paper, which adaptively finds the thresholds for
edge detection depending on block type and the distribution of gradients in each block. A novel method of
computation of high threshold has been proposed in this paper. Block-based hysteresis thresholds are
computed using a non uniform gradient magnitude histogram. The algorithm exhibits remarkably high
edge detection accuracy, scalability and significantly reduced computational time. Pratt’s Figure of Merit
quantifies the accuracy of the edge detector, which showed better values than that of original Canny and
distributed Canny edge detector for benchmark dataset. The method detected all visually prominent edges
for diverse block size.
This paper contain the study about vibration analysis for gearbox casing using finite element analysis
(FEA).The aim of this paper is to apply ANSYS software to determine the natural frequency of gearbox casing. The
objective of the project is to analyze differential gearbox casing of tata indigo cs vehicle for modal and stress
analysis. The theoretical modal analysis needs to be validated with experimental results from Fourier frequency
transformer (FFT) analysis. The main motivation behind the work is to go for a complete FEA of casing rather than
empirical formulae and iterative procedures.
Shadow Detection and Removal in Still Images by using Hue Properties of Color...ijsrd.com
This paper involves the review of the Shadow Detection and Removal in still images. No prior information has been used such as background images etc. for finding the shadows. It is a very challenging issue for the computer vision system that shadows effect the perception of artificial intelligence based machines in appropriately detecting the particular object as shadows also picked by them and detected as false positive objects. Also in surveillance, it affects the proper tracking of humans such as at airports. We proposed a method to remove shadows which eliminates the shadow much better than existed methods. RGB space has been used of the images and some morphological operations also applied to get better results.
A NOVEL APPROACH FOR SEGMENTATION OF SECTOR SCAN SONAR IMAGES USING ADAPTIVE ...ijistjournal
The SAR and SAS images are perturbed by a multiplicative noise called speckle, due to the coherent nature of the scattering phenomenon. If the background of an image is uneven, the fixed thresholding technique is not suitable to segment an image using adaptive thresholding method. In this paper a new Adaptive thresholding method is proposed to reduce the speckle noise, preserving the structural features and textural information of Sector Scan SONAR (Sound Navigation and Ranging) images. Due to the massive proliferation of SONAR images, the proposed method is very appealing in under water environment applications. In fact it is a pre- treatment required in any SONAR images analysis system. The results obtained from the proposed method were compared quantitatively and qualitatively with the results obtained from the other speckle reduction techniques and demonstrate its higher performance for speckle reduction in the SONAR images.
Shadow Detection and Removal Techniques A Perspective Viewijtsrd
Shadow detection and removal from single images of natural scenes is the main problem. Hence, Shadow detection and removal remained a challenging task. Significant research carried out on different shadow detection techniques. Over the last decades several approaches were introduced to deal with shadow detection and removal. Shadows are visual phenomena which happen when an area in the scene is occluded from the primary light source e.g. sun . Shadows are everywhere around us and we are rarely Confused by their presence. This article provides an overview of various methods used for shadow detection and removal using some main components like texture analysis, color information, Gaussian mixture model GMM and deterministic non model based approach. Texture Color This paper is aimed to provide a survey on various algorithms and methods of shadow detection and removal with their comparative study. Avinash Kumar Singh | Ankit Pandit ""Shadow Detection and Removal Techniques: A Perspective View"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25201.pdf
Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/25201/shadow-detection-and-removal-techniques-a-perspective-view/avinash-kumar-singh
International Journal of Engineering Research and Development (IJERD)IJERD Editor
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
Under the certain circumstances of the low and unacceptable accuracy on image recognition, the feature
extraction method for optical images based on the wavelet space feature spectrum entropy is recently
studied. With this method, the principle that the energy is constant before and after the wavelet
transformation is employed to construct the wavelet energy pattern matrices, and the feature spectrum
entropy of singular value is extracted as the image features by singular value decomposition of the matrix.
At the same time, BP neural network is also applied in image recognition. The experimental results show
that high image recognition accuracy can be acquired by using the feature extraction method for optical
images proposed in this paper, which proves the validity of the method.
Removing fence and recovering image details various techniques with performan...RSIS International
In recent world, detection and removal of fences from
digital images become necessary when an important part of the
view changes to be occluded by unnecessary structures. When a
picture is taken, it may have certain structures or objects that
are unwanted. Many scenes such as parks, gardens, and zoos are
secured by fences and people can only take pictures through the
fences. Images or videos taken at open places using lowresolution
cameras, like smart phones are also frequently
corrupted by the presence of occlusions like fences. For the
background occluded by fences, the goal of image de-fencing is to
restore them and return fence-free images. Multi-focus images
are obtained and “defocusing” information is utilized to generate
a clear image. The main aim is when a colored image is input
having fence in the image and then deleting; removing the fence
gives the resultant image with the removal of fence from the
image. Also it involves filling the gaps of removed, damaged
region to recover lost image details. This paper includes various
methods for detection of fence(s), various methods for filling the
gaps, literature survey and performance analysis of methods for
background reconstruction.
Parametric Blur Estimation Using Modified Radon Transform for Natural Images Restoration Vedhapriya Vadhana R – Associate Professor,
Department of ECE,
Maheswari E – PG scholar,
VLSI DESIGN,
Francis Xavier Engineering College, Tirunelveli,India
AN ENHANCED EDGE ADAPTIVE STEGANOGRAPHY APPROACH USING THRESHOLD VALUE FOR RE...ijcsa
This paper attempts to improve the quality and the modification rate of a Stego Image. The input image
provided for estimating the quality of an image and the modified rate is a bitmap image. The threshold
value is used as a parameter for selecting the high frequency pixels from the Cover Image. The data
embedding process are performed on the pixels that are found with the help of Threshold value by using
LSBMR. The quality of an image is estimated by the value of PSNR and the modification rate of an image is
estimated by the value of MSE. The proposed approach achieves about 0.2 to 0.6 % of improvement in the
quality of an image and about 4 to 10 % of improvement in the modification rate of an image compared to
the edge detection techniques such as Sobel and Canny.
Fast nas rif algorithm using iterative conjugate gradient methodsipij
Many improvements on image enhancemen have been achieved by The Non-negativity And Support
constraints Recursive Inverse Filtering (NAS-RIF) algorithm. The Deterministic constraints such as non
negativity, known finite support, and existence of blur invariant edges are given for the true image. NASRIF
algorithms iterative and simultaneously estimate the pixels of the true image and the Point Spread
Function (PSF) based on conjugate gradients method. NAS-RIF algorithm doesn’t assume parametric
models for either the image or the blur, so we update the parameters of conjugate gradient method and the
objective function for improving the minimization of the cost function and the time for execution. We
propose a different version of linear and nonlinear conjugate gradient methods to obtain the better results
of image restoration with high PSNR.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Computationally Efficient Methods for Sonar Image Denoising using Fractional ...CSCJournals
Sonar images produced due to the coherent nature of scattering phenomenon inherit a multiplicative component called speckle and contain almost homogeneous as well as textured regions with relatively rare edges. Speckle removal is a pre-processing step required in applications like the detection and classification of objects in the sonar image. In this paper computationally efficient Fractional Integral Mask algorithms to remove the speckle noise from sonar images is proposed. Riemann- Liouville definition of fractional calculus is used to create Fractional integral masks in eight directions. The use of a mask incorporated with the significant coefficients from the eight directional masks and a single convolution operation required in such case helps in obtaining the computational efficiency. The sonar image heterogeneous patch classification is based on a new proposed naive homogeneity index which depends on the texture strength of the patches and despeckling filters can be adjusted to these patches. The application of the mask convolution only to the selected patches again reduce the computational complexity. The non-homomorphic approach used in the proposed method avoids the undesired bias occurring in the traditional homomorphic approach. Experiments show that the mask size required directly depends on the fractional order. Mask size can be reduced for lower fractional orders thus ensuring the computation complexity reduction for lower orders. Experimental results substantiate the effectiveness of the despeckling method. The different non reference image performance evaluation criterion are used to evaluate the proposed method.
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.
AN ENHANCED BLOCK BASED EDGE DETECTION TECHNIQUE USING HYSTERESIS THRESHOLDING sipij
Edge detection is a crucial step in various image processing systems like computer vision , pattern
recognition and feature extraction. The Canny edge detection algorithm even though exhibits high
accuracy, is computationally more complex compared to other edge detection techniques. A block based
distributed edge detection technique is presented in this paper, which adaptively finds the thresholds for
edge detection depending on block type and the distribution of gradients in each block. A novel method of
computation of high threshold has been proposed in this paper. Block-based hysteresis thresholds are
computed using a non uniform gradient magnitude histogram. The algorithm exhibits remarkably high
edge detection accuracy, scalability and significantly reduced computational time. Pratt’s Figure of Merit
quantifies the accuracy of the edge detector, which showed better values than that of original Canny and
distributed Canny edge detector for benchmark dataset. The method detected all visually prominent edges
for diverse block size.
This paper contain the study about vibration analysis for gearbox casing using finite element analysis
(FEA).The aim of this paper is to apply ANSYS software to determine the natural frequency of gearbox casing. The
objective of the project is to analyze differential gearbox casing of tata indigo cs vehicle for modal and stress
analysis. The theoretical modal analysis needs to be validated with experimental results from Fourier frequency
transformer (FFT) analysis. The main motivation behind the work is to go for a complete FEA of casing rather than
empirical formulae and iterative procedures.
Shadow Detection and Removal in Still Images by using Hue Properties of Color...ijsrd.com
This paper involves the review of the Shadow Detection and Removal in still images. No prior information has been used such as background images etc. for finding the shadows. It is a very challenging issue for the computer vision system that shadows effect the perception of artificial intelligence based machines in appropriately detecting the particular object as shadows also picked by them and detected as false positive objects. Also in surveillance, it affects the proper tracking of humans such as at airports. We proposed a method to remove shadows which eliminates the shadow much better than existed methods. RGB space has been used of the images and some morphological operations also applied to get better results.
A NOVEL APPROACH FOR SEGMENTATION OF SECTOR SCAN SONAR IMAGES USING ADAPTIVE ...ijistjournal
The SAR and SAS images are perturbed by a multiplicative noise called speckle, due to the coherent nature of the scattering phenomenon. If the background of an image is uneven, the fixed thresholding technique is not suitable to segment an image using adaptive thresholding method. In this paper a new Adaptive thresholding method is proposed to reduce the speckle noise, preserving the structural features and textural information of Sector Scan SONAR (Sound Navigation and Ranging) images. Due to the massive proliferation of SONAR images, the proposed method is very appealing in under water environment applications. In fact it is a pre- treatment required in any SONAR images analysis system. The results obtained from the proposed method were compared quantitatively and qualitatively with the results obtained from the other speckle reduction techniques and demonstrate its higher performance for speckle reduction in the SONAR images.
Shadow Detection and Removal Techniques A Perspective Viewijtsrd
Shadow detection and removal from single images of natural scenes is the main problem. Hence, Shadow detection and removal remained a challenging task. Significant research carried out on different shadow detection techniques. Over the last decades several approaches were introduced to deal with shadow detection and removal. Shadows are visual phenomena which happen when an area in the scene is occluded from the primary light source e.g. sun . Shadows are everywhere around us and we are rarely Confused by their presence. This article provides an overview of various methods used for shadow detection and removal using some main components like texture analysis, color information, Gaussian mixture model GMM and deterministic non model based approach. Texture Color This paper is aimed to provide a survey on various algorithms and methods of shadow detection and removal with their comparative study. Avinash Kumar Singh | Ankit Pandit ""Shadow Detection and Removal Techniques: A Perspective View"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25201.pdf
Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/25201/shadow-detection-and-removal-techniques-a-perspective-view/avinash-kumar-singh
International Journal of Engineering Research and Development (IJERD)IJERD Editor
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
Under the certain circumstances of the low and unacceptable accuracy on image recognition, the feature
extraction method for optical images based on the wavelet space feature spectrum entropy is recently
studied. With this method, the principle that the energy is constant before and after the wavelet
transformation is employed to construct the wavelet energy pattern matrices, and the feature spectrum
entropy of singular value is extracted as the image features by singular value decomposition of the matrix.
At the same time, BP neural network is also applied in image recognition. The experimental results show
that high image recognition accuracy can be acquired by using the feature extraction method for optical
images proposed in this paper, which proves the validity of the method.
Removing fence and recovering image details various techniques with performan...RSIS International
In recent world, detection and removal of fences from
digital images become necessary when an important part of the
view changes to be occluded by unnecessary structures. When a
picture is taken, it may have certain structures or objects that
are unwanted. Many scenes such as parks, gardens, and zoos are
secured by fences and people can only take pictures through the
fences. Images or videos taken at open places using lowresolution
cameras, like smart phones are also frequently
corrupted by the presence of occlusions like fences. For the
background occluded by fences, the goal of image de-fencing is to
restore them and return fence-free images. Multi-focus images
are obtained and “defocusing” information is utilized to generate
a clear image. The main aim is when a colored image is input
having fence in the image and then deleting; removing the fence
gives the resultant image with the removal of fence from the
image. Also it involves filling the gaps of removed, damaged
region to recover lost image details. This paper includes various
methods for detection of fence(s), various methods for filling the
gaps, literature survey and performance analysis of methods for
background reconstruction.
Parametric Blur Estimation Using Modified Radon Transform for Natural Images Restoration Vedhapriya Vadhana R – Associate Professor,
Department of ECE,
Maheswari E – PG scholar,
VLSI DESIGN,
Francis Xavier Engineering College, Tirunelveli,India
AN ENHANCED EDGE ADAPTIVE STEGANOGRAPHY APPROACH USING THRESHOLD VALUE FOR RE...ijcsa
This paper attempts to improve the quality and the modification rate of a Stego Image. The input image
provided for estimating the quality of an image and the modified rate is a bitmap image. The threshold
value is used as a parameter for selecting the high frequency pixels from the Cover Image. The data
embedding process are performed on the pixels that are found with the help of Threshold value by using
LSBMR. The quality of an image is estimated by the value of PSNR and the modification rate of an image is
estimated by the value of MSE. The proposed approach achieves about 0.2 to 0.6 % of improvement in the
quality of an image and about 4 to 10 % of improvement in the modification rate of an image compared to
the edge detection techniques such as Sobel and Canny.
Fast nas rif algorithm using iterative conjugate gradient methodsipij
Many improvements on image enhancemen have been achieved by The Non-negativity And Support
constraints Recursive Inverse Filtering (NAS-RIF) algorithm. The Deterministic constraints such as non
negativity, known finite support, and existence of blur invariant edges are given for the true image. NASRIF
algorithms iterative and simultaneously estimate the pixels of the true image and the Point Spread
Function (PSF) based on conjugate gradients method. NAS-RIF algorithm doesn’t assume parametric
models for either the image or the blur, so we update the parameters of conjugate gradient method and the
objective function for improving the minimization of the cost function and the time for execution. We
propose a different version of linear and nonlinear conjugate gradient methods to obtain the better results
of image restoration with high PSNR.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
ALGORITHM AND TECHNIQUE ON VARIOUS EDGE DETECTION: A SURVEYsipij
An edge may be defined as a set of connected pixels that forms a boundary between two disjoints regions.
Edge detection is basically, a method of segmenting an image into regions of discontinuity. Edge detection
plays an important role in digital image processing and practical aspects of our life. .In this paper we
studied various edge detection techniques as Prewitt, Robert, Sobel, Marr Hildrith and Canny operators.
On comparing them we can see that canny edge detector performs better than all other edge detectors on
various aspects such as it is adaptive in nature, performs better for noisy image, gives sharp edges , low
probability of detecting false edges etc
Study and Comparison of Various Image Edge Detection TechniquesCSCJournals
Edges characterize boundaries and are therefore a problem of fundamental importance in image processing. Image Edge detection significantly reduces the amount of data and filters out useless information, while preserving the important structural properties in an image. Since edge detection is in the forefront of image processing for object detection, it is crucial to have a good understanding of edge detection algorithms. In this paper the comparative analysis of various Image Edge Detection techniques is presented. The software is developed using MATLAB 7.0. It has been shown that the Canny’s edge detection algorithm performs better than all these operators under almost all scenarios. Evaluation of the images showed that under noisy conditions Canny, LoG( Laplacian of Gaussian), Robert, Prewitt, Sobel exhibit better performance, respectively. . It has been observed that Canny’s edge detection algorithm is computationally more expensive compared to LoG( Laplacian of Gaussian), Sobel, Prewitt and Robert’s operator
Multitude Regional Texture Extraction for Efficient Medical Image Segmentationinventionjournals
Image processing plays a major role in evaluation of images in many concerns. Manual interpretation of the image is time consuming process and it is susceptible to human errors. Computer assisted approaches for analyzing the images have increased in latest evolution of image processing. Also it has highlighted its performance more in the field of medical sciences. Many techniques are available for the involvement in processing of images, evaluation, extraction etc. The main goal of image segmentation is cluster pixeling the regions corresponding to individual surfaces, objects, or natural parts of objects and to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. The proposed method is to conquer segmentation and texture extraction with Regional and Multitude and techniques involved in it. Ultrasound (US) is increasingly considered as a viable alternative imaging modality in computer-assisted brain segmentation and disease diagnosis applications.First for ultra sound we present region based segmentation.Homogeneous regions depends on image granularity features. Second a local threshold based multitude texture regional seed segmentation for medical image segmentation is proposed. Here extraction is done with dimensions comparable to the speckle size are to be extracted. The algorithm provides a less medical metrics awareness in a minimum user interaction environment. The shape and size of the growing regions depend on look up table entries.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Journals
Abstract In this paper, we present the method of “FPGA implementation of image segmentation by using edge detection based on the sobel edge operator” .due to advancement in computer vision it can be implemented in fpga based architecture. image segmentation separates an image into component regions and object. Segmentation needs to segment the object from the background to read image properly and identify the image carefully. Edge detection is fundamental tool for image segmentation. Sobel edge operator, which is very popular edge detection algorithms, is considered in this work. Sobel method uses the derivative approximation to find edge and perform 2-D spatial gradient measurement for images uses horizontal and vertical gradient matrices .The fpga device providing good performance of integrated circuit platform for research and development. The compact structure of image segmentation into edge detection can be implemented in MAT LAB using VHDL code and the waveform is shown in the model sim.. Keywords: VLSI, FPGA, image segmentation, sobel edge operators, edge detection pixel, mat lab.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Publishing House
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.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
In this paper a novel edge detection method has been proposed which outperform Otsu method [1]. The proposed detection algorithm has been devised using the concept of genetic algorithm in spatial domain. The key of edge detection is the choice of threshold; which determines the results of edge detection. GA has been used to determine an optimal threshold over the image. Results are compared with existing Otsu technique which shows better performances
In this paper a novel edge detection method has been proposed which outperform Otsu method
[1]. The proposed detection algorithm has been devised using the concept of genetic algorithm
in spatial domain. The key of edge detection is the choice of threshold; which determines the
results of edge detection. GA has been used to determine an optimal threshold over the image.
Results are compared with existing Otsu technique which shows better performances.
Hardware Unit for Edge Detection with Comparative Analysis of Different Edge ...paperpublications3
Abstract: An edge in an image is a contour across which the brightness of the image changes abruptly. In image processing, an edge is often interpreted as one class of singularities. Edge detection is an important task in image processing. It is a main tool in pattern recognition, image segmentation, and scene analysis. An edge detector is basically a high pass filter that can be applied to extract the edge points in an image. This topic has attracted many researchers and many achievements have been made. Many researchers provided different approaches based on mathematical calculations which some of them are either robust or cost effective. A new algorithm will be proposed to detect the edges of image with increased robustness and throughput. Using this algorithm we will reduce the time complexity problem which is faced by previous algorithm. We will also propose hardware unit for proposed algorithm which will reduce the area, power and speed problem. We will compare our proposed algorithm with previous approach. For image quality measurement we will use some scientific parameters those are PSNR, SSIM, FSIM. Implementation of proposed algorithm will be done by Matlab and hardware implementation will be done by using of Verilog on Xilinx 14.1 simulator. Verification will be done on Model sim.
Comparative Analysis of Common Edge Detection Algorithms using Pre-processing...IJECEIAES
Edge detection is the process of segmenting an image by detecting discontinuities in brightness. Several standard segmentation methods have been widely used for edge detection. However, due to inherent quality of images, these methods prove ineffective if they are applied without any preprocessing. In this paper, an image pre-processing approach has been adopted in order to get certain parameters that are useful to perform better edge detection with the standard edge detection methods. The proposed preprocessing approach involves median filtering to reduce the noise in image and then edge detection technique is carried out. Finally, Standard edge detection methods can be applied to the resultant pre-processing image and its Simulation results are show that our pre-processed approach when used with a standard edge detection method enhances its performance.
The objective of this paper is to present the hybrid approach for edge detection. Under this technique, edge
detection is performed in two phase. In first phase, Canny Algorithm is applied for image smoothing and in
second phase neural network is to detecting actual edges. Neural network is a wonderful tool for edge
detection. As it is a non-linear network with built-in thresholding capability. Neural Network can be trained
with back propagation technique using few training patterns but the most important and difficult part is to
identify the correct and proper training set.
IMPROVED EDGE DETECTION USING VARIABLE THRESHOLDING TECHNIQUE AND CONVOLUTION...sipij
Medical Field, Robotic vision, Pattern recognition, Hurdle detection, and smart city are examples of areas that require image processing to achieve automation. Detecting an edge is an important stage in any computer vision application. The performance of the edge detecting algorithm is largely affected by the
noise present in an image. An Image with a low signal-to-noise ratio (SNR), imposes a challenge to locate its edges. To improve the observable image boundaries, an adaptive filtering technique is proposed in this article. The proposed algorithm uses convolution of Gabor filter with Gaussian (GoG) operator to clean
the noise before non-Maxima suppression. Furthermore, using variable hysteresis thresholding can further improve edge locating. The implementation of the algorithm was done by Python and Matlab. The obtained
results were compared to a number of reviewed algorithms such as the Canny method, Laplacian of Gaussian, The Marr-Hildreth method, Sobel operator, and the Haar wavelet-based method. Three performance factors were used; PNSR, MSE, and processing time. The simulation result shows that the proposed method has higher PNSR, lower MSE, and shorter processing time when compared to the Canny detector, the Marr-Hildreth, Haar wavelet-based, Laplacian of Gaussian, and the Sobel operator methods. The higher PNSR, lower MSE, and shorter processing time mean improved edge details of the processed image.
Improved Edge Detection using Variable Thresholding Technique and Convolution...sipij
Medical Field, Robotic vision, Pattern recognition, Hurdle detection, and smart city are examples of areas
that require image processing to achieve automation. Detecting an edge is an important stage in any
computer vision application. The performance of the edge detecting algorithm is largely affected by the
noise present in an image. An Image with a low signal-to-noise ratio (SNR), imposes a challenge to locate
its edges. To improve the observable image boundaries, an adaptive filtering technique is proposed in this
article. The proposed algorithm uses convolution of Gabor filter with Gaussian (GoG) operator to clean
the noise before non-Maxima suppression. Furthermore, using variable hysteresis thresholding can further
improve edge locating. The implementation of the algorithm was done by Python and Matlab. The obtained
results were compared to a number of reviewed algorithms such as the Canny method, Laplacian of
Gaussian, The Marr-Hildreth method, Sobel operator, and the Haar wavelet-based method. Three
performance factors were used; PNSR, MSE, and processing time. The simulation result shows that the
proposed method has higher PNSR, lower MSE, and shorter processing time when compared to the Canny
detector, the Marr-Hildreth, Haar wavelet-based, Laplacian of Gaussian, and the Sobel operator methods.
The higher PNSR, lower MSE, and shorter processing time mean improved edge details of the processed
image.
ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Epistemic Interaction - tuning interfaces to provide information for AI support
Iw3515281533
1. Navjot Kaur et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 5, Sep-Oct 2013, pp.1528-1533
RESEARCH ARTICLE
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OPEN ACCESS
An Efficient Edge Detection Approach Based On Pollination
Based Optimization
Navjot Kaur1, Parminder Singh2
1
Research Fellow, 2Asstt. Professor
Chandigarh Engineering College, Landran, Mohali(PB)
1,2
Abstract
Edge detection of pictures is a vital task in computer vision and image processing. Edge detection is always
study focus in the field of medical image processing and analysis. It is necessary step in medical image
processing. Edge detection of noise free pictures is comparatively less complicated, however in most sensible
cases the photographs area unit degraded by noise. Edges in photos provide low-level cues, which could be
utilized in higher level processes, like object detection, recognition, and classification, furthermore as motion
detection, image matching, and trailing. Edges and textures in image are typical samples of high-frequency
information. High-pass filters deduct low-frequency image information and therefore enhance high-frequency
information like edges. Many approaches to image interpretation measure supported edges. This paper proposed
an enhanced edge detection using Pollination based optimization (PBO) algorithm. In this, The samples of
medical images (MRI) with resolution 128×128 is given as input and output as edges of image is produced. All
images are gray scaled and we converted all samples to same size (128×128). In this firstly add speckle noise
then filter this image by using bilateral filter to make image noise free. A bilateral filter preserves sharp edges
by systematically looping through each pixel and adjusting weights to the adjacent pixels accordingly. It extends
the concept of Gaussian smoothing by weighting the filter coefficients with their corresponding relative pixel
intensities. Then we use PBO for edge detection. PBO based edge detection is a new technique and it perform
as well in medical field also and we used MRI images in our work.
Keywords— Edge Detection, Medical field, MRI images, PBO, Bilateral Filter.
I. INTRODUCTION
In many computer vision systems,
orientation and intensity information about edges in
images are used as inputs for further processing to
detect objects. Precise information about edges is
vital to the success of such systems [1]. Information
about edges is widely used in image segmentation,
image registration, image classification and pattern
recognition. Hence, detection of exact edges is a very
important part of image processing algorithms [2].
From an application-level view, an edge
detection algorithm is one which could be able to
provide continuous contours of the object boundaries.
However, the computations required to establish these
continuous contours would be very time consuming
and complex. From a pixel level view, the edges are
the areas of an image where the pixel intensities
undergo a sharp change. These areas shape the
contours which represent the boundary of objects.
Although many edge detection algorithms have been
proposed in the literature over the past three decades
to improve precision of recognized edges, they still
suffer from producing broken edges [3]. A noise
phenomenon is the most important obstacle to the
detection of continuous edges [4].
It causes some variation of pixel intensities
and accordingly reduces the performance of an edge
detection algorithm in noisy images. Another
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important barrier which complicates the operation of
edge detection is illumination phenomenon which
causes the magnitude of the edges in the illuminated
areas to become weak [5]. Since most edge detection
algorithms utilise a thresholding technique to classify
a pixel as an edge or non-edge based on its
magnitude, a pixel with a weak magnitude may be
recognised as non-edge and accordingly the edges
become broken.
Traditional edge detection algorithms are
very fast but they cannot perform well on noisy
images and usually produce broken edges or noise
spots. Advanced edge detection algorithms, which
usually utilise soft computing techniques such as
neural networks and support vector machines for edge
detection, are highly problem-dependent and domain
specific [12].
II. EDGE DETECTION
Edge detection may be a vital space within
the field of pc Vision. Edges outline the boundaries
between regions in a picture that helps with
segmentation and beholding. They’ll show wherever
shadows fall in a picture or the other distinct
modification within the intensity of a picture. Edge
detection may be a basic of low level image process
and sensible edges are necessary for higher level
process. Edge detection refers to the method of
1528 | P a g e
2. Navjot Kaur et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 5, Sep-Oct 2013, pp.1528-1533
characteristic and locating sharp discontinuities in a
picture. The discontinuities or abrupt changes in
element intensity characterize boundaries of objects
during a scene.
Edge Detection Techniques are classified as
follows: the primary order by-product of selection in
image process is that the gradient. The second order
derivatives of selection in image process are typically
computed exploitation Laplacian. For Sobel, a Prewitt
& Roberts technique performs finding edges by
thresholding the gradient for the log. By default edge
perform mechanically computes the edge to use. For
Sobel& Prewitt strategies, we are able to opt to
discover horizontal edges, vertical edges or each.
Laplacian of a Gaussian (LOG) finds edges by
searching for zero crossing once filtering with a
Gaussian filter. Zero crossing finds edges by
searching for Zero crossing once filtering with a userspecified filter. Clever finds by searching for native
maxima of the gradient. The gradient is calculated
exploitation the by-product of a Gaussian filter. The
strategy used 2 thresholds to discover sturdy & weak
edges, and includes the weak edges within the output
provided that they're connected to sturdy edges.
Therefore; this technique is a lot of doubtless to
discover true weak edges. Sobel edge detector
technique is somewhat tough than Prewitt edge
detector. Prewitt edge detector technique is slightly
easier to implement computationally than the Sobel
detector. However it tends to supply somewhat
noisier results. Parliamentarian edge detector is one
amongst the oldest & simplest edge detectors in
digital image process. It’s still used oftentimes in
hardware implementations wherever simplicity &
speed are dominant factors. This detector is employed
significantly but the others. Attributable to partly to
its restricted practicality. Log smoothes the image
(thus reducing noise) and it computes the Laplacian
that yields a double edge image. Zero crossing edge
detector supported same thought because the LOG
technique however the convolution, is disbursed
employing a nominal filter. Clever edge detector is
that the most powerful edge detector provided by
performs edge [2]. The disadvantages of clever edge
detector ar advanced computation, false zerocrossing and time overwhelming [12].
In the system represented in [5], they need
planned
a
unique
methodology
supported
mathematical logic reasoning for edge detection in
digital pictures while not determinant the edge worth.
The planned approach begins by segmenting the
photographs into regions exploitation floating 3x3
binary matrix. an instantaneous fuzzy illation system
mapped a spread of values distinct from one another
within the floating matrix to notice the sting by
exploitation eight planned rules.
In the system represented in [8], they need
planned a brand new edge detection technique
supported the BP neural network. They classified the
sting patterns of binary pictures into sixteen potential
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varieties of visual patterns. Then once coaching the
pre-defined edge patterns, the BP neural network is
applied to corresponds any form of edges with its
connected visual pattern.
Edge detection refers to the method of
characteristic and locating sharp discontinuities in a
picture. The discontinuities area unit abrupt changes
in constituent intensity that characterize boundaries of
objects in a very scene. Classical ways of edge
detection involve convolving the image with associate
degree operator (a 2-D filter), that is made to be
sensitive to massive gradients within the image
whereas returning values of zero in uniform regions.
This can be a particularly sizable amount of edge
detection operators offered, every designed to be
sensitive to bound kinds of edges. Variables
concerned within the choice of a footing detection
operator include:
Edge orientation: The pure mathematics of the
operator determines a characteristic direction
during which it's most sensitive to edges.
Operators are optimized to seem for horizontal,
vertical, or diagonal edges.
Noise environment: Edge detection is
troublesome in screeching pictures, since each
the noise and therefore the edges contain highfrequency content. tries to cut back the noise lead
to blurred and distorted edges. Operators used on
screeching pictures area unit usually larger in
scope, in order that they will average enough
information to discount localized screeching
pixels. This leads to less correct localization of
the detected edges.
Edge structure: Not all edges involve a step
amendment in intensity. Effects like refraction or
poor focus may end up in objects with boundaries
outlined by a gradual amendment in intensity.
The operator has to be chosen to be alert to such
a gradual amendment in those cases. Newer
wavelet-based techniques really characterize the
character of the transition for every draw near
order to tell apart, for instance, edges related to
hair from edges related to a face.
There is a unit many ways to perform edge
detection. However, the bulk of various ways is also
classified into 2 categories:
(i) Gradient: The gradient methodology detects the
sides by craving for the utmost and minimum within
the derivative of the image.
(ii) Laplacian: The Laplacian methodology searches
for zero crossings within the second by-product of the
image to search out edges. a footing has the onedimensional form of a ramp and hard the by-product
of the image will highlight its location.
Clearly, the by-product shows a most placed
at the centre of the sting within the original signal.
This methodology of locating a footing is
characteristic of the “gradient filter” family of edge
detection filters and includes the Sobel methodology.
A constituent location is said a footing location if the
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worth of the gradient exceeds some threshold. As
mentioned before, edges can have higher constituent
intensity values than those encompassing it. Therefore
once a threshold is about, you'll compare the gradient
price to the edge price and sight a footing whenever
the edge is exceeded. What is more, once the primary
by-product is at a most, the second by-product is zero.
As a result, another various to finding the placement
of a footing is to find the zeros within the second byproduct. This methodology is understood because the
Laplacian and therefore the second by-product of the
signal.
The purpose of selecting sharp changes in
image brightness is to capture vital events and
changes in properties of the planet. It is shown that
below rather general assumptions for a picture
formation model, discontinuities in image brightness
area unit seemingly to correspond to:
• Discontinuities thorough,
• Discontinuities in surface orientation,
• Changes in material properties and
• Variations in scene illumination.
III.
Comparison of PBO Results with the previous.
3.2 Basic Block Design
Edges in photos provide low-level cues,
which could be utilized in higher level processes, like
object detection, recognition, and classification,
furthermore as motion detection, image matching, and
trailing. Edges and textures in image are typical
samples of high-frequency information. High-pass
filters deduct low-frequency image information and
therefore enhance high-frequency information like
edges. Many approaches to image interpretation
measure supported edges. Since analysis supported
edge detection is insensitive to vary among the
illumination level.
Start
Upload Image
PROPOSED APPROACH USING PBO
It has been already explained that the Edges
are significant local changes of intensity in an image.
Edge is the boundary between an object and the
background, and identifies the boundary between
overlapping and non-over lapping objects. This means
that if the edges in an image can be identified
accurately, all of the objects can be located and basic
properties such as area, perimeter, and shape can be
measured. Our first problem is to study the edge
detection by using different techniques on different
type of images and need to compare the results in
terms of PSNR, MSE, SSIM & EPI with the
implementation of PBO. In this proposed work we
use Gaussian filter, bilateral filter & trilateral filter to
remove noise. Pollination based optimization (PBO)
based Edge detection is a new technique and we
expect the results of compression to be far better in
comparison to the previous techniques.
3.1 Proposed Model
The proposed model focuses on the above
four objectives which are helpful in improving the
edge detection parameters and are practically
implemented using MATLAB 7.11.0 environment. In
this proposed work, we used Pollination based
optimization algorithm to optimize the results of edge
detection and to form a new technique for edge
detection using PBO. The objectives of our proposed
work are:
Study of Edge Detection.
Study of previous techniques for Edge detection.
Pointing out the pros and cons of the previous
Algorithm.
Study of PBO based Implementation for the same
purpose.
Implementation of PBO based Edge Detection.
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Add noise to Image
Noise Level
40
20
80
60
90
Apply Bilateral Filter
Pollination based
Optimization
End
Fig 1 Basic Block Design of Proposed Work
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Fig 1 shows the basic block design of the proposed
model. The uploaded image is provided with the noise
called speckle noise. We have also tested the code
with the increased and decreased level of noise. Like
we have increased the noise level by twenty, forty and
sixty, eighty and ninety percent of the noise level. By
default the taken noise level is ten percent. The added
noisy image is provided to the Bilateral Filter. Then
filtered image goes to PBO method for edge
detection.
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Image Acquisition (MRI Images)
Add Noise (Speckle)
Remove Noise (Bilateral Filter)
3.3 Algorithm level Design
The algorithm design is shown in Fig 2,
which involves:
Step 1: Image Acquisition (MRI Images).
Initialize PBO Parameters
Step 2: Add Speckle Noise to all images.
Step 3: Remove Noise by using Bilateral Filter.
Step 4: Initialize PBO Parameters.
a=1.2, A=0.9, D=1.2, N41.9, P=2,
Number of Plants = 8,
Number of weeks = 14,
Number of seasons = 8, (number of iterations)
Pollination weekly goal= [0.10 0.25 0.50 0.75
0.90 1.00]
Step 5: Randomly generate vectors.
For season = 1 : number of seasons (iterations)
For week = 1: number of weeks
For k = 1: number of plants
Randomly generate Vectors
Evaluate Reproduction Vector
(R)
Based on R Evaluate Error
Update N, D, A
Step 6: Evaluate Reproduction Vector:
Step 7: Based on R, update number of seasons.
Error Acceptable?
Evaluate Error = Goal - R
Step 8: Based upon error update N, D, A
Step 9: Exit, if Error acceptable.
Edge Detected
Fig 2: Proposed Algorithm level Design using PBO
IV. RESULTS
The samples of medical images (MRI) with
resolution 128×128 is given as input and output as
edges of image is produced. All images are gray
scaled and we converted all samples to same size
(128×128). Results are shown as below:
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5. Navjot Kaur et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 5, Sep-Oct 2013, pp.1528-1533
www.ijera.com
done as per the natural phenomenon of PBO. In this
we use Bilateral filter to remove noise. Then we use
PBO that is pollination based optimization algorithm.
This technique achieves better results.
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Fig 3: Sample Images
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Fig 4: Images with speckle noise
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Fig 5: Testing Images
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Fig 6: Edge Detection using PBO
V. CONCLUSION
The detection of the edge is one of the
important part in the field of Image Processing. In this
paper we proposed an efficient PBO based algorithm
for images edge detection. The detection is basically
www.ijera.com
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www.ijera.com
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