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Research and Implementation of Image Retrieval Based on Color and Texture Feature

Author: YangShuJi
Tutor: ZhouHaiYing
School: University of North
Course: Computer Software and Theory
Keywords: Image Retrieval Feature Extraction Maximum connectivity area histogram Integration of multi-feature image retrieval
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 81
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Abstract


1990s , quickly became a hot spot of research in the field of image information retrieval based on the content of the image retrieval technology . In this paper, the current based on the content of the image retrieval technology development status and existing problems , the following study : This article studies the key technologies involved in content-based image retrieval , including image feature extraction, image indexing techniques relevance feedback technology and image retrieval performance evaluation . Based on research and analysis of the existing color - based image feature extraction algorithm , compared the retrieval performance of several classic color feature extraction algorithm . Global color histogram lost color spatial distribution information of defects , the paper proposes an improved algorithm based on maximum connectivity area histogram , the algorithm can indirectly reflect the spatial distribution characteristics of the color area and keep the color histogram original rotation, translation invariance . Experimental results show that the retrieval performance of the algorithm is much better than the traditional global color histogram . In addition, the existing texture - based image feature extraction algorithm in-depth study . GLCM method through experimental analysis comparing the Gabor wavelet transform method and Tamura texture features of retrieval performance . In order to more accurately describe the image texture features , this paper proposes a texture feature extraction algorithm combined GLCM and Gabor wavelet transform . The experimental results show that , compared to using only a single texture feature extraction algorithm , the improved algorithm proposed in this paper can significantly improve the image retrieval recall and precision . In order to overcome the single visual features of the image content description incomplete , missing part of the image information resulting in low defect system retrieval performance , a fusion of color and texture features image retrieval method , the method more than a single feature - based image retrieval in line with human visual perception , the better retrieval effect . Finally , the use of Microsoft Visual Studio 2010 , Matlab and SQL Server 2000 Design and Implementation of a content-based image retrieval experimental system provides an experimental platform for research .

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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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