A modified Canny edge detector based on weighted least squares

Abstract

Edge detection is the front-end processing stage in most computer vision and image understanding systems. Among various edge detection techniques, Canny edge detector is the one of most commonly used. In this paper a modified Canny edge detection technique focusing on change of the Sobel operator is proposed. Instead of convolution kernels, the weighted least squares method is utilized to calculate the horizontal and vertical gradient. Experimental results show that the new detector can detect some edges which are not observed in the results using the Canny edge detector.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant No. 11701069). And the author thanks for the two anonymous reviewers with their comments about the work.

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Correspondence to Xu Qin.

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National Natural Science Foundation of China (Grant No. 11701069).

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Qin, X. A modified Canny edge detector based on weighted least squares. Comput Stat 36, 641–659 (2021). https://doi.org/10.1007/s00180-020-01017-8

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Keywords

  • Edge detection
  • Gradient
  • Sobel operator
  • Taylor expansion