Title: An intelligent image detection method using improved canny edge detection operator

Authors: Qian Wang; Wenxia Chen; Haiyun Peng

Addresses: College of Computer Science and Technology, Zhoukou Normal University, Zhoukou, Henan, 466001, China ' Zhoukou Senior Technical School, Zhoukou, Henan, 466001, China ' College of Computer Science and Technology, Zhoukou Normal University, Zhoukou, Henan, 466001, China

Abstract: In order to meet the requirement of edge detection of paper disease image in papermaking process, a paper disease image detection method based on improved Canny operator is proposed. Firstly, according to the principle of Gauss filtering and the method of feature statistical analysis, the filtering function and window are selected adaptively. Then, in the gradient solution, the traditional 2 × 2 neighbourhood is replaced by the 3 × 2 or 2 × 3 neighbourhood which enhances the weight of the intermediate pixel, and the accuracy of edge detection is improved by enhancing the influence of the intermediate pixel. Finally, the iterative averaging method is used to determine the optimal threshold and reduce the error rate of image edge segmentation. The experimental results show that this method can effectively detect the edges of paper disease area and has good edge continuity.

Keywords: intelligent image detection; edge detection; improved canny operator; Gauss filtering; feature statistical analysis; adaptive.

DOI: 10.1504/IJITM.2022.126703

International Journal of Information Technology and Management, 2022 Vol.21 No.4, pp.369 - 381

Received: 11 May 2019
Accepted: 09 Feb 2020
Published online: 03 Nov 2022 *

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