Feature point extraction in compressed domain

Renan Coudray; Bernard Besserer; Pierre Courtellemont

doi:10.1117/12.476262

10 January 2003 Feature point extraction in compressed domain

Renan Coudray, Bernard Besserer, Pierre Courtellemont

Proceedings Volume 5021, Storage and Retrieval for Media Databases 2003; (2003) https://doi.org/10.1117/12.476262
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States

Abstract

This document presents several approaches to extract interest points within compressed images (based on DCT compression methods). The goal is to minimize the stages and/or the calculation costs for image sequence indexing tasks or database retrieval from a significant MPEG file repository. Initially, only the fixed images (I-Frames) are take under consideration, motion will be integrated in further research. The traditional invariant feature points (Harris corner points, points with remarquable principal curvatures) are extracted from images using a gradient estimate (first order derivative) or the Laplacian (second-order derivative) of an image. So the first part of this paper handles in detail the derivation of the signal from DCT blocks. The trials to implement feature points detection as close as possible to the DCT coefficient are explained. Results provided by our last DCT-blockwise curvature estimatiorare also shown.

Citation Download Citation

Renan Coudray, Bernard Besserer, and Pierre Courtellemont "Feature point extraction in compressed domain", Proc. SPIE 5021, Storage and Retrieval for Media Databases 2003, (10 January 2003); https://doi.org/10.1117/12.476262

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