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    Abstract:

    How to fast, accurately and effectively segment objects in the color images is the key point in the computer vision and image analysis. This paper introduces a method of region-based color image segmentation. This method first extracts color, texture, and location features for each pixel form integrative feature vectors by selecting suitable color space to form the feature space. In the feature space, the initial cluster center and the number are determined by the improved ISODATA algorithm adaptively, then an image is clustering and separated into regions. Finally, the features of regions are extracted. The experimental results and the comparision with the similar approach are provided. Experimental results show the proposed method has high segmentation speed and good sementation results, and it is fit for region-based image retrieval system and has better application values.

    Reference
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    2 林开颜,吴军辉,徐立鸿.彩色图像分割方法综述.中国图象图形学报, 2005,10(1):1-10.
    3 章毓晋.图像处理和分析.北京:科学出版社, 2003: 180-215.
    4 Carson C, Belongie S, Greenspan H, et al. Blob-world: Image segmentation using expectation-maximization and Its Application to Image Querying. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2002,24 (8):1026-1038.
    5 万建,王继成.基于ISODATA算法的彩色图像分割.计算机工程, 2002,28(5):135-140.
    6 Zhang H, Fritts JE, Goldman SA. A fast texture feature extraction method for region-based image segmen- tation. SPIE Electronic Imaging-Image and Video Communications. 2005,5685:957-968.
    7 Forstner W. A framework for low-level feature extraction. Computer Vision-ECCV'94, Vol. II, Sweden: J. O. Eklundh, 1994.383-394.
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张语涵,孙劲光,苗锡奎.基于改进的ISODATA算法彩色图像分割.计算机系统应用,2010,19(2):41-45

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  • Received:April 27,2009
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