earticle

논문검색

Study on Defects Edge Detection in Infrared Thermal Image Based on Ant Colony Algorithm

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

저자정보

  • TANG Qingju School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin, 150001, P.R.China, School of Mechanical Engineering, Heilongjiang University of Science and Technology, Harbin, 150022, P.R.China
  • DAI Jingmin School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin, 150001, P.R.China
  • LIU Chunsheng School of Mechanical Engineering, Heilongjiang University of Science and Technology, Harbin, 150022, P.R.China
  • LIU Yuanlin School of Mechanical Engineering, Heilongjiang University of Science and Technology, Harbin, 150022, P.R.China
  • REN Chunping School of Mechanical Engineering, Heilongjiang University of Science and Technology, Harbin, 150022, P.R.China

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.