Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 490840, 14 pages
Research Article

Adaptive Binary Arithmetic Coder-Based Image Feature and Segmentation in the Compressed Domain

1Department of Computer Science and Information Engineering, National United University, Miaoli 36003, Taiwan
2Department of Electronics Engineering, Chung Hua University, Hsinchu City 30012, Taiwan
3Department of Mathematics, University of Salerno, Via Ponte Don Melillo, 84084 Fisciano, Italy

Received 31 August 2011; Accepted 23 September 2011

Academic Editor: Ming Li

Copyright © 2012 Hsi-Chin Hsin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Image compression is necessary in various applications, especially for efficient transmission over a band-limited channel. It is thus desirable to be able to segment an image in the compressed domain directly such that the burden of decompressing computation can be avoided. Motivated by the adaptive binary arithmetic coder (MQ coder) of JPEG2000, we propose an efficient scheme to segment the feature vectors that are extracted from the code stream of an image. We modify the Compression-based Texture Merging (CTM) algorithm to alleviate the influence of overmerging problem by making use of the rate distortion information. Experimental results show that the MQ coder-based image segmentation is preferable in terms of the boundary displacement error (BDE) measure. It has the advantage of saving computational cost as the segmentation results even at low rates of bits per pixel (bpp) are satisfactory.