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has been cited by the following article:

• TITLE: Restricted Hysteresis Reduce Redundancy in Edge Detection

  AUTHORS: Bo Li, Ulrik Söderström, Shafiq Ur Réhman, Haibo Li

  KEYWORDS: Edge Detection; Hysteresis; Non-Maximum Suppression; Redundancy

  JOURNAL NAME: Journal of Signal and Information Processing, Vol.4 No.3B, October 17, 2013

  ABSTRACT: In edge detection algorithms, there is a common redundancy problem, especially when the gradient direction is close to -135°, -45°, 45°, and 135°. Double edge effect appears on the edges around these directions. This is caused by the discrete calculation of non-maximum suppression. Many algorithms use edge points as feature for further task such as line extraction, curve detection, matching and recognition. Redundancy is a very important factor of algorithm speed and accuracy. We find that most edge detection algorithms have redundancy of 50% in the worst case and 0% in the best case depending on the edge direction distribution. The common redundancy rate on natural images is approximately between 15% and 20%. Based on Canny’s framework, we propose a restriction in the hysteresis step. Our experiment shows that proposed restricted hysteresis reduce the redundancy successfully.