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An Evaluation of Color-Spatial Retrieval Techniques for Large Image Databases

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Abstract

In a color-spatial retrieval technique, the color information is integrated with the knowledge of the colors' spatial distribution to facilitate content-based image retrieval. Several techniques have been proposed in the literature, but these works have been developed independently without much comparison. In this paper, we present an experimental evaluation of three color-spatial retrieval techniques—the signature-based technique, the partition-based algorithm and the cluster-based method. We implemented these techniques and compare them on their retrieval effectiveness and retrieval efficiency. The experimental study is performed on an image database consisting of 12,000 images. With the proliferation of image retrieval mechanisms and the lack of extensive performance study, the experimental results can serve as guidelines in selecting a suitable technique and designing a new technique.

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  1. Department of Computer Science, School of Computing, National University of Singapore, 3 Science Drive 2, Singapore, 117543

    Kian-Lee Tan, Beng Chin Ooi & Chia Yeow Yee

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  1. Kian-Lee Tan
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  2. Beng Chin Ooi
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Tan, KL., Ooi, B.C. & Yee, C.Y. An Evaluation of Color-Spatial Retrieval Techniques for Large Image Databases. Multimedia Tools and Applications 14, 55–78 (2001). https://doi.org/10.1023/A:1011359607594

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