This paper addresses the segmentation problem in noisy image based on Fast Edge Integration (FEI) method in active contour model (ACM) and proposes a new statistical active contour model (SACM). Two modifications are performed in FEI method. First, in order to handle noisy images, maximum log-likelihood estimation is used to replace the minimal variance term proposed by Chan and Vese. Second, a penalising term is employed to replace the time consuming re-initialization process. The proposed SACM is evaluated and compared with the existing ACM-based algorithms in terms of segmentation results and computational time. The proposed SACM outperforms existing methods and requires much less computational time.


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    Titel :

    A New Statistical Active Contour Model for Noisy Image Segmentation


    Beteiligte:
    Chen, Bo (Autor:in) / Yuen, Pong-Chi (Autor:in) / Lai, Jian-Huang (Autor:in) / Chen, Wen-Sheng (Autor:in)


    Erscheinungsdatum :

    2008-05-01


    Format / Umfang :

    495334 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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