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Visual Feature Extraction under Wavelet Domain for Image Retrieval

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Abstract:

In this paper, we propose a new visual feature extraction method for content-based image retrieval (CBIR) based on wavelet transform which has both spatial-frequency and multi-resolution characteristics. We extract visual features for each frequency band in wavelet transformation and use them for CBIR. The lowest frequency band involves utilizing the spatial information of an original image. We extract 64 feature vectors using fuzzy homogeneity in the wavelet domain, which considers both the wavelet coefficients and the spatial information of each coefficient. In addition, we extract 3 feature vectors using the energy values of high frequency bands, and store those to the image database. As a query, we retrieve the most similar image from the image database according to the 10 largest homograms (normalized fuzzy homogeneity vectors) and 3 energy values. Simulation results show that the proposed method has good accuracy in image retrieval using 90 texture images.

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Periodical:

Key Engineering Materials (Volumes 277-279)

Pages:

206-211

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.277-279.206

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Online since:

January 2005

Authors:

Won Bae Park, Eun Ju Ryu, Young Jun Song, Jae Hyeong Ahn

Keywords:

Feature Extraction, Fuzzy, Image Retrieval, Wavelet

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© 2005 Trans Tech Publications Ltd. All Rights Reserved

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