Image indexing technique using entropy measures with multilevel multiresolution approach

Tae-Hee Kim; Dong-Seok Jeong

doi:10.1117/12.298447

23 December 1997 Image indexing technique using entropy measures with a multilevel multiresolution approach

Tae-Hee Kim, Dong-Seok Jeong

Proceedings Volume 3312, Storage and Retrieval for Image and Video Databases VI; (1997) https://doi.org/10.1117/12.298447
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

Abstract

In this paper, we propose a new content-based indexing algorithm that utilizes pixel-wise entropy and extracts features such as color and entropy from an image as indices. We propose a technique that fulfills both global and regional searching. Global searching scheme utilizes entropy features with multilevel-multiresolution. As resolution of the image is reduced, another information of the image is revealed. As gray-level of the image is reduced, we see how large the gray- level differences are between neighboring pixels. Regional searching utilizes color features that are extracted from regions separated by entropy measures. Our algorithm provides not only the automated extraction of entropy-based regions but also the representation of their color contents. Thus, we can classify images using entropy and multiresolution multi-level based features. Various experiments show the promising future of the proposed algorithm.

Citation Download Citation

Tae-Hee Kim and Dong-Seok Jeong "Image indexing technique using entropy measures with a multilevel multiresolution approach", Proc. SPIE 3312, Storage and Retrieval for Image and Video Databases VI, (23 December 1997); https://doi.org/10.1117/12.298447

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