Wednesday 20th of September 2017
 

Combined Local and Global Features for Improving the Shape Retrieval


Mohamed Eisa

Content-based image retrieval (CBIR) is playing an important role in multimedia information retrieval. This paper proposes an effective solution for IR by combining shape description and feature matching. First, an effective shape description method which includes two shape descriptors is presented. Second, an effective feature matching strategy to compute the dissimilarity value between the feature vectors extracted from images is proposed. Finally, we combine the shape description method and the feature matching strategy to realize our solution. A large number of experiments are carried out to evaluate the system performance over five standard databases, which represent various kinds of images. The results reveal that the proposed descriptors and the strategy of distance measure outperform the existing methods of image retrieval

Keywords: content-based image retrieval, features extraction, similarity measures.

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ABOUT THE AUTHOR

Mohamed Eisa
Computer Science Department, Port Said University 42526 Port Said, Egypt


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