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Line Segment Detection with Hough Transform Based on Minimum Entropy

  • Zezhong Xu
  • Bok-Suk Shin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8333)

Abstract

The Hough transform is a popular technique used in the field of image processing. In this paper, fitting and interpolation techniques are employed to compute high-accuracy peak parameters by considering peak spreading. The entropy is selected to measure the scatter-degree of voting. The voting in each column is considered as a random variable and voting values are considered as a probabilistic distribution. The corresponding entropies are computed and used to estimate the peak parameters. Endpoint coordinates of a line segment are computed by fitting a sine curve with more cells. It is more accurate and robust compared to solving directly two equations. The proposed method is tested on simulated and real images.

Keywords

Hough transform peak detection entropy endpoints 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Zezhong Xu
    • 1
    • 2
  • Bok-Suk Shin
    • 1
  1. 1.Department of Computer ScienceThe University of AucklandAucklandNew Zealand
  2. 2.College of Computer Information EngineeringChangzhou Institute of Technology ChangzhouJiangsuChina

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