Translator Disclaimer
Paper
7 May 2003 Feature transformation in compressed domain for content-based image retrieval
Author Affiliations +
Proceedings Volume 5022, Image and Video Communications and Processing 2003; (2003) https://doi.org/10.1117/12.476501
Event: Electronic Imaging 2003, 2003, Santa Clara, CA, United States
Abstract
This paper addresses the problem of image content characterization in the compressed domain for the purpose of facilitating similarity matching in a multimedia database. Specifically, given the disparity of the content characterization power of compressed domain approaches and those based on pixel-domain features, with the latter being usually considered as the more superior one, our objective is to transform the selected set of compressed domain feature histograms in such a way that the retrieval result based on these features is compatible with their spatial domain counterparts. Since there are a large number of possible transformations, we adopt a genetic algorithm approach to search for the optimal one, where each of the binary strings in the population represents a candidate transformation. The fitness of each transformation is defined as a function of the discrepancies between the spatial-domain and compressed-domain retrieval results. In this way, the GA mechanism ensures that transformations which best approximate the performance of spatial domain retrieval will survive into the next generation and are allowed through the operations of crossover and mutation to generate variations of themselves to further improve their performances.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hau-San Wong, Horace H.S. Ip, and Chun-Ip Chiu "Feature transformation in compressed domain for content-based image retrieval", Proc. SPIE 5022, Image and Video Communications and Processing 2003, (7 May 2003); https://doi.org/10.1117/12.476501
PROCEEDINGS
9 PAGES


SHARE
Advertisement
Advertisement
RELATED CONTENT

Multimedia search engine with relevance feedback
Proceedings of SPIE (December 20 2001)
Image categorization using N x M grams
Proceedings of SPIE (January 15 1997)
Case for image querying through image spots
Proceedings of SPIE (January 01 2001)

Back to Top