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3 November 2005 A color image segmentation algorithm based on multiresolution and fuzzy similarity
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Proceedings Volume 6044, MIPPR 2005: Image Analysis Techniques; 604403 (2005)
Event: MIPPR 2005 SAR and Multispectral Image Processing, 2005, Wuhan, China
This paper describes an efficient algorithm for color image segmentation based on a multiresolution application of a wavelet transform and watershed segmentation algorithm. The procedure toward complete segmentation consists of four steps: pyramid representation, image segmentation, region projection and region merging. First, pyramid representation creates multiresolution images using a wavelet transform. Second, image segmentation segments the lowest-resolution image of the pyramid using a watershed segmentation algorithm. Third, the segmented low-resolution image with label is projected into a full-resolution image (original image) by inverse wavelet transform. Finally, region merging merges the segmented regions using fuzzy similarity. Experimental results of the presented method can be applied to the segmentation of noise or degraded images as well as reduce over-segmentation.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jianli Ding, Yuanxiang Li, and Lingling Wang "A color image segmentation algorithm based on multiresolution and fuzzy similarity", Proc. SPIE 6044, MIPPR 2005: Image Analysis Techniques, 604403 (3 November 2005);


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