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Restoration of Images Corrupted by High Density Salt & Pepper Noise through A...
Abstract: In this paper an efficient algorithm is proposed for removal of salt & pepper noise from digital images. Salt and pepper noise in images is present due to bit errors in transmission or introduced during the signal acquisition stage. It represents itself as randomly occurring white and black pixels. This noise can be removed using standard Median Filter (SMF), Progressive Switched Median Filter (PSMF) under low density noise conditions. Decision Based Algorithm (DBA) and Modified Decision Based Unsymmetric Trimmed Median Filter (MDBUTMF) do not give better results at high noise density. So, in this project, this drawback will be overcome by using Adaptive Median based Modified Mean Filter (AMMF). This proposed algorithm shows better Peak Signal-to-Noise Ratio and clear image than the existing algorithm. Keywords- Median filter, Progressive Switched Median Filter, Decision Based Algorithm, Modified Decision Based Unsymmetric Trimmed Median Filter
Evaluation of Wash and Light Fastness of Some Selected Printed Fabrics
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change in colour and staining using the grey scale. The change in colour of the tested specimen and the staining
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light fastness property. The specimen and the blue standard were exposed behind a glass and inserted into the
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J017134853
This document presents a methodology for shape-based leaf categorization using image processing and computer vision techniques. The proposed approach involves binarizing leaf images, detecting corners using Harris corner detection, determining the convex hull, calculating internal angles, and comparing angle arrays to match input leaves to those in a database. Experimental results on test images demonstrate the ability of the method to retrieve matching leaf images despite geometric transformations of the input. Future work will involve analyzing leaf vein structures for more accurate classification.
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This document discusses image segmentation techniques using clustering algorithms. It introduces Fuzzy C-Means (FCM) clustering, which allows data points to belong to multiple clusters with varying degrees of membership. However, FCM does not work well on noisy or non-linearly separable data. The document proposes the Kernel Fuzzy C-Means (KFCM) algorithm, which uses a kernel function to map data to a higher dimensional space, making separation easier. While improving results for noisy images, KFCM does not consider neighboring pixels. Finally, the document introduces the Novel Modified Kernel Fuzzy C-Means (NMKFCM) algorithm, which incorporates neighborhood information into the objective function to further improve segmentation accuracy, especially for noisy images
A Decisive Filtering Selection Approach For Improved Performance Active Noise...
Abstract : In this work we present a filtering selection approach for efficient ANC system. Active noise cancellation (ANC) has wide application in next generation human machine interaction to automobile Heating Ventilating and Air Conditioning (HVAC) devices. We compare conventional adaptive filters algorithms LMS, NLMS, VSLMS, VSNLMS, VSLSMS for a predefined input sound file, where various algorithms run and result in standard output and better performance. The wiener filter based on least means squared (LMS) algorithm family is most sought after solution of ANC. This family includes LMS, NLMS, VSLMS, VSNLMS, VFXLMS, FX-sLMS and many more. Some of these are nonlinear algorithm, which provides better solution for nonlinear noisy environment. The components of the ANC systems like microphones and loudspeaker exhibit nonlinearities themselves. The nonlinear transfer function create worse situation. This is a task which is some sort of a prediction of suitable solution to the problems. The Radial Basis Function of Neural Networks (RBF NN) has been known to be suitable for nonlinear function approximation [1]. The classical approach to RBF implementation is to fix the number of hidden neurons based on some property of the input data, and estimate the weights connecting the hidden and output neurons using linear least square method. So an efficient novel decisive approach for better performing ANC algorithms has been proposed. Keywords - Adaptive filters, Winner filter ANC, Least mean square, N LMS, VSNLMS, RBF.
Characteristics of Life
The document outlines the key characteristics of life, including cellular organization, homeostasis, metabolism, growth and development, adaptation, response to stimuli, reproduction, and heredity. It explains that all living things share these characteristics and lists examples of each one. The document also discusses how organisms inherit genetic information from parents and how life is sustained through reproduction and development.
Characteristics of life notes review
The document discusses the six main characteristics of life: organization, growth and development, reproduction, response to stimuli, homeostasis, and use of energy. It provides descriptions and examples for each characteristic. All living things share these traits, which include being made of one or more cells, the ability to grow, reproduce, respond to changes internally and externally, regulate internal conditions, and obtain and use energy.
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Restoration of Images Corrupted by High Density Salt & Pepper Noise through A...
Abstract: In this paper an efficient algorithm is proposed for removal of salt & pepper noise from digital images. Salt and pepper noise in images is present due to bit errors in transmission or introduced during the signal acquisition stage. It represents itself as randomly occurring white and black pixels. This noise can be removed using standard Median Filter (SMF), Progressive Switched Median Filter (PSMF) under low density noise conditions. Decision Based Algorithm (DBA) and Modified Decision Based Unsymmetric Trimmed Median Filter (MDBUTMF) do not give better results at high noise density. So, in this project, this drawback will be overcome by using Adaptive Median based Modified Mean Filter (AMMF). This proposed algorithm shows better Peak Signal-to-Noise Ratio and clear image than the existing algorithm. Keywords- Median filter, Progressive Switched Median Filter, Decision Based Algorithm, Modified Decision Based Unsymmetric Trimmed Median Filter
Evaluation of Wash and Light Fastness of Some Selected Printed Fabrics
Abstract: The printed fabrics were subjected to ISO2, ISO3, and ISO4 wash fastness test and assessed for
change in colour and staining using the grey scale. The change in colour of the tested specimen and the staining
of the adjacent undyed cloths were assessed with the appropriate grey scales. The fabrics were also tested for
light fastness property. The specimen and the blue standard were exposed behind a glass and inserted into the
light fastness testing machine. Exposure was carried out for 48 hours. Based on the research carried out, it was
found that the selected foreign fabrics show a higher wash and light fastness property as compared to the local
fabrics which also show high wash and light fastness property.
J017134853
This document presents a methodology for shape-based leaf categorization using image processing and computer vision techniques. The proposed approach involves binarizing leaf images, detecting corners using Harris corner detection, determining the convex hull, calculating internal angles, and comparing angle arrays to match input leaves to those in a database. Experimental results on test images demonstrate the ability of the method to retrieve matching leaf images despite geometric transformations of the input. Future work will involve analyzing leaf vein structures for more accurate classification.
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This document discusses image segmentation techniques using clustering algorithms. It introduces Fuzzy C-Means (FCM) clustering, which allows data points to belong to multiple clusters with varying degrees of membership. However, FCM does not work well on noisy or non-linearly separable data. The document proposes the Kernel Fuzzy C-Means (KFCM) algorithm, which uses a kernel function to map data to a higher dimensional space, making separation easier. While improving results for noisy images, KFCM does not consider neighboring pixels. Finally, the document introduces the Novel Modified Kernel Fuzzy C-Means (NMKFCM) algorithm, which incorporates neighborhood information into the objective function to further improve segmentation accuracy, especially for noisy images
A Decisive Filtering Selection Approach For Improved Performance Active Noise...
Abstract : In this work we present a filtering selection approach for efficient ANC system. Active noise cancellation (ANC) has wide application in next generation human machine interaction to automobile Heating Ventilating and Air Conditioning (HVAC) devices. We compare conventional adaptive filters algorithms LMS, NLMS, VSLMS, VSNLMS, VSLSMS for a predefined input sound file, where various algorithms run and result in standard output and better performance. The wiener filter based on least means squared (LMS) algorithm family is most sought after solution of ANC. This family includes LMS, NLMS, VSLMS, VSNLMS, VFXLMS, FX-sLMS and many more. Some of these are nonlinear algorithm, which provides better solution for nonlinear noisy environment. The components of the ANC systems like microphones and loudspeaker exhibit nonlinearities themselves. The nonlinear transfer function create worse situation. This is a task which is some sort of a prediction of suitable solution to the problems. The Radial Basis Function of Neural Networks (RBF NN) has been known to be suitable for nonlinear function approximation [1]. The classical approach to RBF implementation is to fix the number of hidden neurons based on some property of the input data, and estimate the weights connecting the hidden and output neurons using linear least square method. So an efficient novel decisive approach for better performing ANC algorithms has been proposed. Keywords - Adaptive filters, Winner filter ANC, Least mean square, N LMS, VSNLMS, RBF.
Characteristics of Life
The document outlines the key characteristics of life, including cellular organization, homeostasis, metabolism, growth and development, adaptation, response to stimuli, reproduction, and heredity. It explains that all living things share these characteristics and lists examples of each one. The document also discusses how organisms inherit genetic information from parents and how life is sustained through reproduction and development.
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The document discusses the six main characteristics of life: organization, growth and development, reproduction, response to stimuli, homeostasis, and use of energy. It provides descriptions and examples for each characteristic. All living things share these traits, which include being made of one or more cells, the ability to grow, reproduce, respond to changes internally and externally, regulate internal conditions, and obtain and use energy.
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