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The Research on Object Matching Based on Major Color Spectrum and Spatial Distribution Entropy

Author: SunQianFeng
Tutor: HuDong
School: Nanjing University of Posts and Telecommunications
Course: Signal and Information Processing
Keywords: Target Matching Kmeans clustering Main color spectrum The spatial distribution of entropy
CLC: TP391.41
Type: Master's thesis
Year: 2012
Downloads: 14
Quote: 0
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Abstract


As the field of intelligent transportation, medical, security and other urgent needs, multi-camera collaborative intelligent monitoring key technology more and more attention, which mainly include target detection and localization, target match, target handover and objectives behavior analysis and other technical . The target matching technology as a multi-camera collaborative bridge in recent years has also become a hot and difficult research in the field of intelligent monitoring. The main target matching method, first introduced the common goal of matching, and in-depth analysis of the object matching method based on color feature, for computationally intensive and not take into account the color spatial distribution information related method, the target does not match accurate, and other problems, this article from the following studies: (1) a description of the main color spectrum based on the the two center optimization and M-Kmeans fusion target algorithm. That is in Kmeans clustering algorithms cluster in order to reduce the computational complexity of the target color, first with two center optimization algorithm to determine the cluster initial center point, then M-Kmeans algorithm class members in the clustering process adjustment. Research and experimental results show that the fusion algorithm not only improves the accuracy of the description of the color spectrum of the target host, and reduce the sensitivity of the clustering results of the initial centers, improve the stability of the clustering results. (2) the spatial distribution of the main color spectrum entropy technology. That target the main color spectrum, based on the distribution ratio of the corresponding pixel in a different division of the region, the application of Shannon entropy formula calculated the entropy of the main component of the color spectrum to represent its space segment information. The experimental results show that the distribution of entropy can well distinguish target the main color spectrum histogram similar but different target color space distribution through the the main color spectrum space. (3) Based on the first two points results MCS-SDE (Major Color Spectrum and Spatial Distribution Entropy) target matching method. Main color spectrum color similarity calculation, using the spectral components of the space distribution the entropy similarity model weighted to calculate the target match. And discussed in the final match MCS-SDE-based target multi-frame joint matching method. Finally, a summary of the content of the research, and the subject further research direction prospect.

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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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