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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/81291

    Title: Extracting and Labelling the Objects from an Image by Using the Fuzzy Clustering Algorithm and a New Cluster Validity
    Authors: Chou, Chien-Hsing;Hsieh, Yi-Zeng;Su, Mu-Chun;Chu, Yung-Long
    Contributors: 淡江大學電機工程學系
    Keywords: extract object;cluster validity;clustering algorithm;line symmetry;similarity measure
    Date: 2013-02-25
    Issue Date: 2013-03-07 16:53:53 (UTC+8)
    Publisher: IACSIT Press
    Abstract: Many real-world and man-made objects are line symmetry. To detection the line-symmetry objects from an image, in this paper, a new cluster validity measure which adopts a non-metric distance measure based on the idea of "line symmetry" is presented. The thresholding technique is first applied to extract the objects from the original image; and the object pixels are transferred to be the data patterns. Then the fuzzy clustering algorithm is applied to label the object pixels; and the proposed validity measure is used in determining the number of objects. Simulation results are used to illustrate the performance of the proposed measure.
    Relation: 2013 2nd International Conference on Information Computer Application (ICICA 2013), 3p.
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Proceeding

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