In this paper, a fuzzy weighted active contour model for synthetic aperture radar image segmentation is proposed. A feature-based approach comprising weighted active contours and level set segmentation is used to improve segmentation results. A fuzzy inference engine is used to assign weights to pixels of the level set function based on local entropy and local variance. Experiment results show that the proposed scheme improves the segmentation efficiency and accuracy as compared with the existing region-scalable fitting scheme.


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    Title :

    SAR image segmentation based on active contours with fuzzy logic


    Contributors:


    Publication date :

    2016-02-01


    Size :

    1690189 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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