Stereo matching is one of the key steps of 3D reconstruction based on binocular vision. In order to improve the convergence speed and accuracy in 3D reconstruction based on binocular vision, this paper adopts the comb...
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Stereo matching is one of the key steps of 3D reconstruction based on binocular vision. In order to improve the convergence speed and accuracy in 3D reconstruction based on binocular vision, this paper adopts the combination method of polar constraint and ant colony algorithm. By using the line constraint to reduce the search range, an ant colony algorithm is used to optimize the stereo matching feature search function in the proposed search range. Through the establishment of the stereo matching optimization process analysis model of ant colony algorithm, the global optimization solution of stereo matching in 3D reconstruction based on binocular vision system is realized. The simulation results show that by the combining the advantage of polar constraint and ant colony algorithm, the stereo matching range of 3D reconstruction based on binocular vision is simplified, and the convergence speed and accuracy of this stereo matching process are improved.
Increase in traffic density along with the population growth in the world has resulted in more and more congested roads, air pollution, and accidents. Growth of total number of vehicles around the world has increased ...
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In this paper, we focus on denoising of additively corrupted volumetric magnetic resonance (MR) images for improved clinical diagnosis and further processing. We have considered three dimensional MR images as third-or...
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In this paper, a hybrid model for detecting text regions from scene images as well as document image is presented. At first, background is suppressed to isolate foreground regions. Then, morphological operations are a...
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To understand the profundity of the subject in importance, revision of previous work has always played a vigorous role in developing interest and curiosity. For morphological assessment and measurement of quantitative...
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In-1 recent years, science technology has developed rapidly, phenotypic analysis of modal animals plays a vital role in the study of human life andcomputervision technology is an indispensable part of modal animal p...
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ISBN:
(纸本)9781450365123
In-1 recent years, science technology has developed rapidly, phenotypic analysis of modal animals plays a vital role in the study of human life andcomputervision technology is an indispensable part of modal animal phenotype analysis. With the speed of computer operation has been significantly improved, some novel computervision technologies emerged based on visible images. Due to higher adaptability of the complex environments under the visible light shine, the automation and efficiency of work has greatly promoted by computervision technology, and it can effectively avoid the error arising from manual operation. In this paper, we mainly summarize the research progress in the image aspects of computervision technology for the existing methods into three groups, namely, (1) image preprocessing;(2) image feature extraction;(3) image classification. Based on depth analysis of methods, we explore the image analysis method of modal animal phenotypic representation through solving different problem.
Multimodal medical image fusion techniques are utilized to fuse two images obtained from dissimilar sensors for obtaining additional information. These methods are used to fuse computed tomography (CT) images with mag...
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In today’s world, image sharing has been a vital area of digital industry. images are transmitted over an insecure transmission channel and are vulnerable to possible attacks. In this paper, we propose a novel techni...
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As web, mobile, desktop and all other applications use image for different purposes, image compression technique has become one of the most important applications in image analysis as well as in computer science. Thou...
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In this work, we propose a three-phase convolutional neural network-based approach for word spotting in handwritten text documents. The system uses a reconstructive convolutional neural network model for segmentation ...
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