Content-Based Image Retrieval Using Features Extracted From Halftoning-Based Block Truncation Coding

• Published in: IEEE transactions on image processing Vol. 24; no. 3; pp. 1010 - 1024
• Main Authors: Jing-Ming Guo, Prasetyo, Heri
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Arrays; Band-pass filters; Bit Pattern Feature; Color Co-occurrence feature; Content-Based Image Retrieval; Feature extraction; Image coding; Image color analysis; Image retrieval; Indexing; Ordered Dither Block Truncation Coding; ordered dither block truncation coding; Bit pattern feature; content-based image retrieval; color co-occurrence feature
• ISSN: 1057-7149; 1941-0042; 1941-0042
• DOI: 10.1109/TIP.2014.2372619

This paper presents a technique for content-based image retrieval (CBIR) by exploiting the advantage of low-complexity ordered-dither block truncation coding (ODBTC) for the generation of image content descriptor. In the encoding step, ODBTC compresses an image block into corresponding quantizers and bitmap image. Two image features are proposed to index an image, namely, color co-occurrence feature (CCF) and bit pattern features (BPF), which are generated directly from the ODBTC encoded data streams without performing the decoding process. The CCF and BPF of an image are simply derived from the two ODBTC quantizers and bitmap, respectively, by involving the visual codebook. Experimental results show that the proposed method is superior to the block truncation coding image retrieval systems and the other earlier methods, and thus prove that the ODBTC scheme is not only suited for image compression, because of its simplicity, but also offers a simple and effective descriptor to index images in CBIR system.