Back to Search
Start Over
An Anti-Noise Fast Circle Detection Method Using Five-Quadrant Segmentation
- Source :
- Sensors, Vol 23, Iss 5, p 2732 (2023)
- Publication Year :
- 2023
- Publisher :
- MDPI AG, 2023.
-
Abstract
- Extracting circle information from images has always been a basic problem in computer vision. Common circle detection algorithms have some defects, such as poor noise resistance and slow computation speed. In this paper, we propose an anti-noise fast circle detection algorithm. In order to improve the anti-noise of the algorithm, we first perform curve thinning and connection on the image after edge extraction, then suppress noise interference by the irregularity of noise edges and extract circular arcs by directional filtering. In order to reduce the invalid fitting and speed up the running speed, we propose a circle fitting algorithm with five quadrants, and improve the efficiency of the algorithm by the idea of “divide and conquer”. We compare the algorithm with RCD, CACD, WANG and AS on two open datasets. The results show that we have the best performance under noise while keeping the speed of the algorithm.
- Subjects :
- circle detection
anti-noise
five-quadrant segmentation
Chemical technology
TP1-1185
Subjects
Details
- Language :
- English
- ISSN :
- 23052732 and 14248220
- Volume :
- 23
- Issue :
- 5
- Database :
- Directory of Open Access Journals
- Journal :
- Sensors
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.4f19a2989004d0ca0ee4a8dd2fd8c97
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/s23052732