An intelligent image detection method using improved canny edge detection operator

Qian Wang, Wenxia Chen and Haiyun Peng

International Journal of Information Technology and Management, 2022, vol. 21, issue 4, 369-381

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. (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=126703 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijitma:v:21:y:2022:i:4:p:369-381

Access Statistics for this article

More articles in International Journal of Information Technology and Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().