Robust color image segmentation by Karhunen-Loeve transform based Otsu multi-thresholding and K-Means Clustering

Chenxue Wang*, Junzo Watada

*この研究の対応する著者

    研究成果: Conference contribution

    7 被引用数 (Scopus)

    抄録

    In this paper, a novel fast approach is proposed to achieve image segmentation in color image. This method helps to refine the foreground regions and achieves the goal of robust color image segmentation throw the following four steps. First, modified Karhunen-Loeve transform is performed to reduce the redundant component, thus selecting the most important part of the color images. Second, a multi-threshold Otsu method is carried out to select the best thresholds from image histogram. Thereby, the conventional Otsu method has been extended from gray level to color level. Third, improved Sobel edge detection is added to enhance the weight of edge detail of the foreground image. Finally, a K-Means Clustering is used to merge the over-segmented regions. Experimental results prove that this method has a good performance even when the color image has a complicated structure in the background.

    本文言語English
    ホスト出版物のタイトルProceedings - 2011 5th International Conference on Genetic and Evolutionary Computing, ICGEC 2011
    ページ377-380
    ページ数4
    DOI
    出版ステータスPublished - 2011
    イベント5th International Conference on Genetic and Evolutionary Computing, ICGEC2011 - Xiamen
    継続期間: 2011 8 292011 9 1

    Other

    Other5th International Conference on Genetic and Evolutionary Computing, ICGEC2011
    CityXiamen
    Period11/8/2911/9/1

    ASJC Scopus subject areas

    • 計算理論と計算数学
    • コンピュータ サイエンスの応用

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