원문정보
보안공학연구지원센터(IJSIP)
International Journal of Signal Processing, Image Processing and Pattern Recognition
Vol.9 No.4
2016.04
pp.121-130
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Edge extraction is an important part in the detection of infrared thermal images. Ant colony algorithm has the characteristics of high efficiency, high noise suppression, and comprehensive information of edge information. The basic principle of ant colony algorithm is analyzed. An ant colony optimization algorithm for image edge detection is established. And to have defective parts for analysis of infrared thermography The ant colony algorithm and the classical Canny operator are compared and analyzed. The experimental results show that the algorithm has high efficiency, comprehensive information and high computational efficiency.
목차
Abstract
1. Introduction
2. Ant Colony Algorithm
3. Image Edge Detection Algorithm Based on Ant Colony Optimization
3.1 Initial Ant Distribution
3.2 Transfer Probability
3.3 Transfer rule
3.4 Pheromone Update
3.5 Edge Extraction
4. Experimental Simulation and Analysis
4.1 Experimental System
4.2 Specimen
4.3 Defects Edge Detection
Conclusion
Acknowledgments
References
1. Introduction
2. Ant Colony Algorithm
3. Image Edge Detection Algorithm Based on Ant Colony Optimization
3.1 Initial Ant Distribution
3.2 Transfer Probability
3.3 Transfer rule
3.4 Pheromone Update
3.5 Edge Extraction
4. Experimental Simulation and Analysis
4.1 Experimental System
4.2 Specimen
4.3 Defects Edge Detection
Conclusion
Acknowledgments
References
저자정보
참고문헌
자료제공 : 네이버학술정보
