Content-based image retrieval using Generic Fourier Descriptor and Gabor Filters

Content-based image retrieval (CBIR) is an important research area with application to large amount image databases and multimedia information. CBIR has three general visual contents, including color, texture and shape. The focus of this paper is on the problem of shape and texture feature extraction and representation for CBIR. We apply Generic Fourier Descriptor (GFD) for shape feature extraction and Gabor Filters (GF) for texture feature extraction, and we successfully combine GFD and GF together for shape and texture feature extraction. Experimental results show that the proposed GFD+GF is robust to all the test databases with best retrieval rate.