Title :
Content-based image retrieval with ordered dither block truncation coding features
Author :
Jing-Ming Guo ; Prasetyo, Heri
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
Abstract :
This paper presents a technique for Content-Based Image Retrieval (CBIR) by exploiting the low complexity advantage of the Ordered-Dither Block Truncation Coding (ODBTC) for generating image content descriptors. The two image features, namely Color Co-occurrence Feature (CCF) and Bit Pattern Features (BPF), are generated from ODBTC encoded data streams (without really performing an image compression or decoding process) to measure the similarity between two images. Experimental results show that the proposed method is superior to the Block Truncation Coding (BTC) image retrieval system and other former methods, and prove that the ODBTC scheme is not only suited for image compression for its simplicity, but also offers a conveniently way for image indexing in the content-based image retrieval system.
Keywords :
data compression; feature extraction; image coding; image retrieval; BPF; CBIR; CCF; ODBTC encoded data streams; bit pattern features; block truncation coding features; color cooccurrence feature; content based image retrieval; decoding process; image compression; image content descriptors; image indexing; ordered dither block truncation coding; Bit Pattern Feature; Color Co-occurrence Feature; Content-Based Image Retrieval; Ordered Dither Block Truncation Coding;
Conference_Titel :
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location :
Melbourne, VIC
DOI :
10.1109/ICIP.2013.6738825