| Title | Overview of edge detection algorithms based on mathematical morphology |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Dong, Yeting, Wang, Zhiwen, Guo, Wuyuan |
| Conference Name | 2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC ) |
| Date Published | oct |
| Keywords | composability, Deep Learning, edge detection, feature extraction, Image edge detection, Industries, machine vision, Market research, mathematical morphology, Metrics, Morphology, multiscale and multidirectional, pubcrawl, resilience, Resiliency, Scalability, security, structural elements |
| Abstract | Edge detection is the key and difficult point of machine vision and image processing technology. The traditional edge detection algorithm is sensitive to noise and it is difficult to accurately extract the edge of the image, so the effect of image processing is not ideal. To solve this problem, people in the industry use the structural element features of morphological edge detection operator to extract the edge features of the image by carefully designing and combining the structural elements of different sizes and directions, so as to effectively ensure the integrity of edge information in all directions and eliminate large noise at the same time. This paper first introduces the traditional edge detection algorithms, then summarizes the edge detection algorithms based on mathematical morphology in recent years, finds that the selection of multi-scale and multi-directional structural elements is an important research direction, and finally discusses the development trend of mathematical morphology edge detection technology. |
| DOI | 10.1109/IAEAC54830.2022.9930043 |
| Citation Key | dong_overview_2022 |
Overview of edge detection algorithms based on mathematical morphology