Deformation tolerant generalized Hough transform for sketch-based image retrieval in complex scenes
Image and Vision Computing
An improved Hough transform voting scheme utilizing surround suppression
Pattern Recognition Letters
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In this paper, we present a new method for two-dimensional (2D) shape detection applicable under affine transformation. The problem of affine-invariant shape detection is an important and fundamental research subject in computer vision. Although various methods have been proposed to solve this problem, most of those approaches are not well suited for the following general cases: (1) a shape to be detected is occluded by other overlapping objects, (2) a shape boundary is partially broken because of noise or other factors. We introduce a new method to deal with such cases, which extends the generalized Hough transform [1] to be an affine-invariant shape detector. This method, called the affine-GHT, utilizes pairwise parallel tangents and basic properties of an affine transformation to carry the direct computation for six parameters of an affine transformation. Experimental result demonstrates that the proposed method performs successfully and efficiently.