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Accurate tracking method for gray image target in complex scenes

Author: LiuBinJie
Tutor: JinGang
School: University of Electronic Science and Technology
Course: Control Theory and Control Engineering
Keywords: target tracking local binary pattern combining characteristic weighted histogram mean shift particle filtering
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 25
Quote: 0
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Abstract


The imaging tracking technique is a challenging task in the field of computer vision. The purpose of this dissertation is to study the real-time target tracking technology of grayscale image under complex background.Based on the synopsis about the technology development tendency, the difficulty of the target tracking is discussed. Some basic techniques, such as image segmentation and filtering methods etc, are studied in details.Based on the analysis of the texture extraction for target detection, a new texture extraction method of LBP is proposed, for improving the accuracy of the target characteristics description.A special attention is focused at the study of grayscale imaging target tracking technique, based on the histogram algorithm and mean shift. Due to color information lack and the partially similarity between target and background, the tracking point would be easily shift in the grayscale images, a new algorithm is suggested to resolve this problem. The target model is described by the combining characteristic weighted histogram, the analogical degree measurement is determined by the Bhattacharyya coefficient, and the target poison is located through the mean shift. In order to improve the precision of tracking, the particle filtering and the mean shift are combined. The test results show that the proposed algorithm is able to locate the imaging target precisely in sequence images while the target is moving swiftly under complex background.

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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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