Abstract
In this paper, we present a novel and efficient scheme for extracting, indexing and retrieving color images. Our motivation was to reduce the space overhead of partition-based approaches taking advantage of the fact that only a relatively low number of distinct values of a particular visual feature is present in most images. To extract color feature and build indices into our image database we take into consideration factors such as human color perception and perceptual range, and the image is partitioned into a set of regions by using a simple classifying scheme. The compact color feature vector and the spatial color histogram, which are extracted from the seqmented image region, are used for representing the color and spatial information in the image. We have also developed the region-based distance measures to compare the similarity of two images. Extensive tests on a large image collection were conducted to demonstrate the effectiveness of the proposed approach.
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Foundation item: Supported by the National High Technology Development of China (863-511-920-001)
Biography: Cao Kui(1963-), male, Ph. D. candidate, Professor, research direction: multimedia database, high dimensional index technique.
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Kui, C., Yu-cai, F. Integrating color and spatial feature for content-based image retrieval. Wuhan Univ. J. Nat. Sci. 7, 290–296 (2002). https://doi.org/10.1007/BF02912143
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DOI: https://doi.org/10.1007/BF02912143
Key words
- color distribution
- spatial color histogram
- region-based
- image representation and retrieval
- similarity matching
- integrating of single features