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Proceedings Paper

Direct feature extraction from compressed images
Author(s): Bo Shen; Ishwar K. Sethi
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Paper Abstract

This paper examines the issue of direct extraction of low level features from compressed images. Specifically, we consider the detection of areas of interest and edges in images compressed using the discrete cosine transform (DCT). For interest areas, we show how a measure based on certain DCT coefficients of a block can provide an indication of underlying activity. For edges, we show using an ideal edge model how the relative values of different DCT coefficients of a block can be used to estimate the strength and orientation of an edge. Our experimental results indicate that coarse edge information from compressed images can be extracted up to 20 times faster than conventional edge detectors.

Paper Details

Date Published: 13 March 1996
PDF: 11 pages
Proc. SPIE 2670, Storage and Retrieval for Still Image and Video Databases IV, (13 March 1996); doi: 10.1117/12.234779
Show Author Affiliations
Bo Shen, Wayne State Univ. (United States)
Ishwar K. Sethi, Wayne State Univ. (United States)

Published in SPIE Proceedings Vol. 2670:
Storage and Retrieval for Still Image and Video Databases IV
Ishwar K. Sethi; Ramesh C. Jain, Editor(s)

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