Abstract—Content-Based Image Retrieval (CBIR) allows automatically extracting target images according to objective visual contents of the image itself. Content-based image retrieval has many application areas such as, education, commerce, military, searching, biomedicine and web image classification. This paper proposes a new image retrieval system, which uses color and texture information to form the feature vectors and Bhattacharyya distance and new similarity measure to perform the feature matching. This framework integrates the ycbcr color histogram which represents the global feature and edge histogram as local descriptor to enhance the retrieval results. The proposed technique is proper for precisely retrieving images even in deformation cases such as geometric deformations and noise. It is tested on a standard image databases such as Wang and UCID databases. Experimental work shows that the proposed approach improves the precision and recall of retrieval results compared to other approaches reported in literature.
Index Terms—CBIR, image retireval, EHD, FCTH, MPEG7, YCbCr
M. H. Saad is with the National Center for Radiation Research and Technology, Cairo, Egypt (e-mail: m.hassansaad@ gmail.com).
H. I. Saleh, is with the National Center for Radiation Research and Technology, Cairo, Egypt (e-mail: h_i_saleh@ hotmail.com).
H. Konbor, is with the Alazhar University, Cairo, Egypt (e-mail: m.hassansaad@ gmail.com).
M. Ashour, is with the National Center for Radiation Research and Technology, Cairo, Egypt (e-mail: ma_ashour@ hotmail.com).
Cite: M. H. Saad, H. I. Saleh, H. Konbor, and M. Ashour, "Image Retrieval based on Integration between YCbCrColor Histogram and Texture Feature," International Journal of Computer Theory and Engineering vol. 3, no. 5, pp. 701-706, 2011.
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