A content-based image retrieval system based on object-moment feature |
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Authors: | K.-F. Hwang K.-Y. Chung |
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Affiliation: | Department of Computer Science and Information EngineeringNational Taichung University of Science and Technology, Taichung, Taiwan |
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Abstract: | The last decade has witnessed great interest in research on content-based image retrieval (CBIR). In 2009, Lin et al. proposed a smart CBIR system based on colour and texture feature. Their system has a high detection rate except the cases where image objects have similar shapes. To enhance the detection rate a shape-based image feature called object-moment is proposed in this paper. Object-moment uses the moment of force to compute the object edge feature by calculating the distance from each edge pixel to the axis, and adding them up as a feature. Besides, we integrate the colour features (NSOM, CSOM) and the texture features (CCM, DBPSP) to enhance image detection rate and simplify computation of image retrieval. A series of analyses and comparisons are performed in our experiments to demonstrate that our proposed method improves the retrieval accuracy significantly. |
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Keywords: | Content-based image retrieval Texture feature Edge feature |
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