An extension of the generalized Hough transform to realize affine-invariant two-dimensional (2D) shape detection
作者： A. Kimura , T. Watanabe
DOI: 10.1109/ICPR.2002.1044613
关键词: Noise shaping 、 Object detection 、 Hough transform 、 Affine shape adaptation 、 Boundary (topology) 、 Computer vision 、 Affine transformation 、 Mathematics 、 Harris affine region detector 、 Affine combination 、 Algorithm 、 Artificial intelligence
摘要: We present a method for two-dimensional (2D) shape detection applicable under affine transformation. The problem of affine-invariant is an important and fundamental research subject in computer vision. Although various methods have been proposed to solve this problem, most those approaches are not well suited the following general cases: (1) be detected occluded by other overlapping objects, (2) boundary partially broken because noise or factors. introduce deal with such cases, which extends generalized Hough transform detector. This method, called affine-GHT, utilizes pairwise parallel tangents basic properties transformation carry direct computation six parameters Experimental results demonstrate that performs successfully efficiently.
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