• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.1
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• pp.11-24
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• 2008

Region-based image retrieval techniques, which divide image into similar regions having similar characteristics and examine similarities among divided regions, were proposed to support an efficient low-dimensional color indexing scheme. However, color image segmentation techniques are required additionally. The problem of segmentation is difficult because of a large variety of color and texture. It is known to be difficult to identify image regions containing the same color-texture pattern in natural scenes. In this paper we propose an automatic color image segmentation algorithm. The colors in each image are first quantized to reduce the number of colors. The gray level of image representing the outline edge of image is constructed in terms of Fisher's multi-class linear discriminant on quantized images. The gray level of image is transformed into a binary edge image. The edge showing the outline of the binary edge image links to the nearest edge if disconnected. Finally, the final segmentation image is obtained by merging similar regions. In this paper we design and implement a region-based image retrieval system using the proposed segmentation. A variety of experiments show that the proposed segmentation scheme provides good segmentation results on a variety of images.