Mongolian pattern image processing based on improved Canny algorithm

Shuzhen Li; Yunli Bai; Zhijun Shen; Bin Fan; Junjie Chen

doi:10.1117/12.2656797

20 October 2022 Mongolian pattern image processing based on improved Canny algorithm

Shuzhen Li, Yunli Bai, Zhijun Shen, Bin Fan, Junjie Chen

Proceedings Volume 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022); 1245124 (2022) https://doi.org/10.1117/12.2656797
Event: 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 2022, Chongqing, China

Abstract

In view of the complexity and long time required of the current Mongolian pattern handwritten sketch, an improved Canny operator is proposed to extract the vectorized edge of the Mongolian pattern, use the adaptive median filter to denoise the image, calculate the gradient size and direction combined with the Sobel template, and detect and connect the edge based on the adaptive threshold combined with iteration and Otsu (Otsu method). The experimental results show that the improved Canny operator has an average improvement of 25.7% and 13.6% over the traditional edge detection operator in SSIM (structural similarity) and PSNR (peak signal-to-noise ratio), respectively.

Citation Download Citation

Shuzhen Li, Yunli Bai, Zhijun Shen, Bin Fan, and Junjie Chen "Mongolian pattern image processing based on improved Canny algorithm", Proc. SPIE 12451, 5th International Conference on Computer Information Science and Application Technology (CISAT 2022), 1245124 (20 October 2022); https://doi.org/10.1117/12.2656797

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