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Proceedings Paper

Image compression based on motion segmentation
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Paper Abstract

Humans subjectively evaluate the content of a scene. FOr content-based indexing and retrieval, we index and retrieve the scene containing moving objects because they remain in our memory longer than static scene. The importance of processing moving objects has been demonstrated in image compression, content-based data processing, and a variety of video processing techniques. This paper proposes the method of segmenting and then compressing the image including moving objects. The image scene is usually composed of the motion region (MR) and static region (SR). For simplicity, the camera motion region is assigned to the SR, because the region has similar characteristics with the SR. The MR is extracted by our segmentation technique. We propose a line scan-based segmentation method being composed of motion estimation and label assignment. The dominant region owning the largest number of blocks with the same label is classified as SR. The region excluding the SR is MR. Then, the MR is processed by lossless compression or lossy with low-compression ratio to preserve the high quality, and the SR by a lossy method with high compression ratio. Rather than applying separate methods to MR and SR, we use a hybrid compression method based on DCT. Experiments on test video clips show the increase of the compression ratio with respect to the lossless compression and better visualization of the moving objects compared with the lossy compression.

Paper Details

Date Published: 6 October 1997
PDF: 12 pages
Proc. SPIE 3229, Multimedia Storage and Archiving Systems II, (6 October 1997); doi: 10.1117/12.290359
Show Author Affiliations
Man-Bae Kim, Samsung Advanced Institute of Technology (South Korea)
Do-Kyoon Kim, Samsung Advanced Institute of Technology (South Korea)

Published in SPIE Proceedings Vol. 3229:
Multimedia Storage and Archiving Systems II
C.-C. Jay Kuo; Shih-Fu Chang; Venkat N. Gudivada, Editor(s)

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