A novel model-based unified approach is proposed for generating a set of image feature maps (or primal sketches). For each type of feature, a parametric model is developed to characterize the local intensity function in an image. Projections of intensity profile onto a set of orthogonal Zernike moment-generating polynomials are used to estimate model-parameters and in turn generate the desired feature map. A small set of moment-based detectors is identified that can extract various kinds of primal sketches from intensity as well as range images. One main advantage of using parametric model-based techniques is that it is possible to extract complete information (i.e., model parameters) about the underlying image feature, which is desirable in many high-level vision tasks. Experimental results are included to demonstrate the effectiveness of the proposed feature detectors.<>


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    Title :

    Zernike moment-based feature detectors


    Contributors:
    Ghosal, S. (author) / Mehrotra, R. (author)


    Publication date :

    1994-01-01


    Size :

    486327 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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