This paper considers the problem of modeling and extracting arbitrary deformable contours from noisy images. We propose a global contour model based on a stable and regenerative shape matrix, which is invariant and unique under rigid motions. Combined with Markov random field to model local deformations, this yields prior distribution that exerts influence over a global model while allowing for deformations. We then cast the problem of extraction into posterior estimation and show its equivalence to energy minimization of a generalized active contour model. We discuss pertinent issues in shape training, minimax regularization and initialization by generalized Hough transform. Finally, we present experimental results and compare its performance to rigid template matching.<>


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    Title :

    Deformable contours: modeling and extraction


    Contributors:
    Lai (author) / Chin (author)


    Publication date :

    1994-01-01


    Size :

    600673 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Deformable Contours: Modeling and Extraction

    Lai, K. F. / Chin, R. T. / Institute of Electrical and Electronics Engineers; Computer Society | British Library Conference Proceedings | 1994



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    Fundana, K. / Overgaard, N. C. / Heyden, A. | British Library Online Contents | 2008