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Pattern recognition and computer vision in the realization of

Author: ZhangHongBo
Tutor: JinYuanYu
School: Qingdao University of Science and Technology
Course: Control Theory and Control Engineering
Keywords: Pattern Recognition Support Vector Machine Partition distortion correction Image Segmentation Hough transform
CLC: TP391.41
Type: Master's thesis
Year: 2009
Downloads: 214
Quote: 3
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Abstract


Pattern recognition and artificial intelligence as information science an important part in real life has been widely used. In the field of pattern recognition , support vector regression function very successfully deal with the problem and pattern recognition problems , the main contents of this paper is how to pattern recognition SVM applied to computer vision , finally realize the application system . In this paper, man-machine chess pawn in the system identified as targets , utilization of image processing, computer interface , software programming and pattern recognition techniques . Radial number of pixels in pieces feature vectors by SVM classification pawn , pawn overcome malposition does not recognize the situation , and achieved good recognition results. This paper studied the Hough transform theory and support vector machine algorithm, mainly including the Hough transform for circle detection to improve and support vector machine principle and processing steps. Then began the process of identifying pieces : ( 1 ) image acquisition is generated when the geometric distortion affects the recognition accuracy and speed , this article from both theory and experiment to find a suitable partition of this article distortion correction algorithm, so that the images collected effect of greatly improved ( 2 ) Since the red and black chess pawn there is some common characters , the need for the red and black chess pawn different strategies were used for image segmentation ( 3 ) images in a grid positioned on pieces based on the Hough transform for circle through near the detection principle in the grid coordinates for precise positioning pieces ( 4 ) with support vector machines for all the pieces identified . Finally realize System. Practice has proved that through the system , with the support vector machine to identify exactly the right pieces to meet the system requirements. In addition , the paper also for support vector machines to implement other computer vision to provide a reference .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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