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http://dx.doi.org/10.5302/J.ICROS.2002.8.6.455

Object-Based Image Search Using Color and Texture Homogeneous Regions  

유헌우 (고려대학교 산업시스템정보공학과)
장동식 (고려대학교 산업시스템정보공학과)
서광규 (KIST CAD/CAM연구센터)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.8, no.6, 2002 , pp. 455-461 More about this Journal
Abstract
Object-based image retrieval method is addressed. A new image segmentation algorithm and image comparing method between segmented objects are proposed. For image segmentation, color and texture features are extracted from each pixel in the image. These features we used as inputs into VQ (Vector Quantization) clustering method, which yields homogeneous objects in terns of color and texture. In this procedure, colors are quantized into a few dominant colors for simple representation and efficient retrieval. In retrieval case, two comparing schemes are proposed. Comparing between one query object and multi objects of a database image and comparing between multi query objects and multi objects of a database image are proposed. For fast retrieval, dominant object colors are key-indexed into database.
Keywords
image segmentation; color; texture; VQ clustering; object-based image retrieval; content-based image retrieval; key-indexed;
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