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1. CONTENT-BASED IMAGE RETRIEVAL USING FEATURES EXTRACTED FROM
HALFTONING-BASED BLOCK TRUNCATION CODING
ABSTRACT
A technique for content-basedimage retrieval (CBIR) by exploiting the advantage of
lowcomplexityordered-dither block truncation coding (ODBTC) forthe generation of image
content descriptor. In the encodingstep, ODBTC compresses an image block into corresponding
quantizes and bitmap image. Two image features are proposedto index an image, namely, color
co-occurrence feature (CCF) andbit pattern features (BPF), which are generated directly from
theODBTC encoded data streams without performing the decodingprocess. The CCF and BPF of
an image are simply derived from the two ODBTC quantizes and bitmap, respectively, by
involvingthe visual codebook. Experimental results show that the proposedmethod is superior to
the block truncation coding image retrievalsystems and the other earlier methods, and thus prove
that theODBTC scheme is not only suited for image compression, becauseof its simplicity, but
also offers a simple and effective descriptorto index images in CBIR system.