imageprocessing and analysis is a useful tool for monitoring of activated sludge wastewater treatment plants. However, its effectiveness is dependent on performance of the segmentation algorithms. The activated sludg...
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ISBN:
(纸本)9781509011810
imageprocessing and analysis is a useful tool for monitoring of activated sludge wastewater treatment plants. However, its effectiveness is dependent on performance of the segmentation algorithms. The activated sludge wastewater plant can be monitored by imageprocessing and analysis of images acquired through microscope using bright field microscopy and phase contrast microscopy. In this paper, we have investigated three segmentation algorithms which are channel based segmentation, edge based segmentation and Bradley based segmentation. The performance of the algorithms is assessed using the performance metric of accuracy. Forty gold approximations of ground truth images are manually prepared for comparing with the result for segmentation. Half of the forty images are acquired at lOx and rest at 20x objective magnification of the microscope. Edge based segmentation gives better results compared to other algorithms with accuracy of 0.972.
A camera with an image sensor is an important alternative device to a photodiode-based receiver of visible-light communication in outdoor scenarios. The intrinsic color separation capability of a camera qualifies colo...
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A camera with an image sensor is an important alternative device to a photodiode-based receiver of visible-light communication in outdoor scenarios. The intrinsic color separation capability of a camera qualifies color shift keying (CSK) modulation as an intuitive solution to enhance the achievable data rate. The symbol error rate (SER) of CSK modulation is considerably important to system design and performance evaluation, and has not been extensively investigated for outdoor optical camera communication systems from the viewpoint of camera-based channel and imageprocessing-based demodulation. In this study, a two-level channel model is proposed to characterize CSK transmission in a single pixel and in the entire image. A general framework of SER analysis for arbitrary CSK constellations was proposed by directly calculating the upper bounds from the empirical distribution of the noise light in the CIE 1931 color space. Through numerical simulations, the influence of the image detector on CSK demodulation was evaluated. The results indicated that an accurate target region is important for maintaining the SER, and an enlarged target region is beneficial when the maximum ratio combination and selective combination algorithms are used in pixel combination.
Practical sparse approximation algorithms (particularly greedy algorithms) suffer two significant drawbacks: they are difficult to implement in hardware, and they are inefficient for time-varying stimuli (e.g., video)...
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ISBN:
(纸本)9781424414369
Practical sparse approximation algorithms (particularly greedy algorithms) suffer two significant drawbacks: they are difficult to implement in hardware, and they are inefficient for time-varying stimuli (e.g., video) because they produce erratic temporal coefficient sequences. We present a class of locally competitive algorithms (LCAs) that correspond to a collection of sparse approximation principles minimizing a weighted combination of reconstruction MSE and a coefficient cost function. These systems use thresholding functions to induce local nonlinear competitions in a dynamical system. Simple analog hardware can implement the required nonlinearities and competitions. We show that our LCAs are stable under normal operating conditions and can produce sparsity levels comparable to existing methods. Additionally, these LCAs can produce coefficients for video sequences that are more regular (i.e., smoother and more predictable) than the coefficients produced by greedy algorithms.
Automated image registration based on pattern recognition is a critical procedure in many applications of machine vision and is essential for accurate navigation and change detection. In this paper;an overview of the ...
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ISBN:
(纸本)0819448117
Automated image registration based on pattern recognition is a critical procedure in many applications of machine vision and is essential for accurate navigation and change detection. In this paper;an overview of the specific applications of image registration in wafer inspection is given, followed by a case study in the application of image registration for direct to digital holography (DDH) wafer inspection. A complete system of novel algorithms for holographic image registration is then presented. In the case of DDH system with complex data flows, the proposed registration system is capable of accepting a variety of data streams as inputs: (1) complex frequency data;(2) complex spatial data;(3) magnitude data extracted from holograms;(4) phase data extracted from holograms;and (5) intensity-only data. This flexibility facilitates the development of faster, more reliable, and more efficient DDH processingsystems, which is important in system optimization and production. In particular, the system enables the use of the full complex wavefront, which contains both reflectance and structural topology information, in the registration process. The added information contained in the wavefront can be utilized for increased robustness and computational efficiency. Both the theory and implementation of the proposed registration system are briefly described within the framework of DDH processing for wafer inspection tasks. Several examples of defect detection and wafer alignment are given with estimates of accuracy and robustness.
Aiming at the problems of blurred contrast and difficult diagnosis of vascular tissue in medical images, A nonlinear transform blood vessel enhancement method based on guided filtering is proposed. In this paper, a hy...
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Many different piecewise-quadratic bases are in existence, but they cannot be used practically since the method for calculation of factors in these bases have not been developed. This work is hardware-oriented method,...
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ISBN:
(纸本)9788022728560
Many different piecewise-quadratic bases are in existence, but they cannot be used practically since the method for calculation of factors in these bases have not been developed. This work is hardware-oriented method, that allows the use of existing algorithms of fast transformations based on Haar and Harmut's orthogonal step-function for the calculation of coefficients both piecewise-linear, and piecewise-quadratic bases factors.
In this paper, the comparison between deep learning methods and feature extraction algorithms is presented. The principle of Grey-Level Co-occurrence Matrix (GLCM) and its modifications are used for our research. The ...
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ISBN:
(纸本)9781728175393
In this paper, the comparison between deep learning methods and feature extraction algorithms is presented. The principle of Grey-Level Co-occurrence Matrix (GLCM) and its modifications are used for our research. The main idea was to design a method for the description of combined features and textures. The texture classification process is carried out with the robust support vector machine classifier (SVM). We compare these feature extraction methods with proposed Convolutional Neural Networks (CNN). This proposed network contains 25 layers. Finally, the all evaluation and comparison of color texture retrieval results for all used methods are presented. The all feature extraction algorithms and proposed CNN have been tested on two different color texture datasets (Outex and Vistex datasets).
Extending digital imageprocessingalgorithms to the triangular mesh is always an important idea for triangular mesh processing. This paper presented a sphere image representation of triangular mesh and used it for tr...
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Mainly digital images are under sampled. It is the same for SPOT digital image satellite. The very meaning is that the instrument is too much powerful for this sampling. The worth side effect is that artifacts (aliasi...
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ISBN:
(纸本)0819441880
Mainly digital images are under sampled. It is the same for SPOT digital image satellite. The very meaning is that the instrument is too much powerful for this sampling. The worth side effect is that artifacts (aliasing) are introduced in the image, the good side is that images can be improved if the sampling density is increased. In this paper we use images from the two HRVIR instruments onboard SPOT1-4 satellite to multiply by a factor two the density and the resolution of the image.
The Hyperspectral image Analysis Toolbox (HAT) is a collection of algorithms that extend the capability of the MATLAB numerical computing environment for the processing of hyperspectral and multispectral imagery. The ...
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ISBN:
(纸本)0819457914
The Hyperspectral image Analysis Toolbox (HAT) is a collection of algorithms that extend the capability of the MATLAB numerical computing environment for the processing of hyperspectral and multispectral imagery. The purpose of the HIAT Toolbox is to provide information extraction algorithms to users of hyperspectral and multispectral imagery in environmental and biomedical applications. MAT has been developed as part of the NSF Center for Subsurface Sensing and Imaging (CenSSIS) Solutionware that seeks to develop a repository of reliable and reusable software tools that can be shared by researchers across research domains. MAT provides easy access to supervised and unsupervised classification algorithms developed at LARSIP over the last 8 years.
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