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http://dx.doi.org/10.22156/CS4SMB.2017.7.3.073

Generalized Hough Transform using Internal Gradient Information  

Chang, Ji Young (Department of Computer Engineering, Gwangju University)
Publication Information
Journal of Convergence for Information Technology / v.7, no.3, 2017 , pp. 73-81 More about this Journal
Abstract
The generalized Hough transform (GHough) is a useful technique for detecting and locating 2-D model. However, GHough requires a 4-D parameter array and a large amount of time to detect objects of unknown scale and orientation because it enumerates all possible parameter values into a 4-D parameter space. Several n-to-1 mapping algorithms were proposed to reduce the parameter space from 4-D to 2-D. However, these algorithms are very likely to fail due to the random votes cast into the 2-D parameter space. This paper proposes to use internal gradient information in addition to the model boundary points to reduce the number of random votes cast into 2-D parameter space. Experimental result shows that our proposed method can reduce both the number of random votes cast into the parameter space and the execution time effectively.
Keywords
Computer Vision; Hough Transform; Generalized Hough Transform; Arbitrary Shape Detection; Object Recognition;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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