Earticle

초록

영어

The traditional Harris corner detection algorithm is sensitive to scale change, corners detected throughout the entire image under complex background, thus extracting more false corners, lead to the follow-up of large amount of calculation and a high rate of error matching. To solve this problem, this paper proposes an optimized Harris corner detection algorithm. First, a significant region detection method is used to extract the target area, and take closing operation for the result figure, can effectively achieve target and background segmentation; second, scale invariant describing methods is applied to Harris algorithm, at the same time, combined with the non-maximum suppression methods to extract corners, get more right corners. Through experiment contrasts, the algorithm used in this paper can be improved more corner detection performance.

목차

Abstract
 1. Introduction
 2. Harris Corner Detection Algorithm
 3. The Improved Harris Corner Detection Algorithm
  3.1. Significant Region Detection Method
  3.2. The Scale Invariant Harris Corner Detection Algorithm
 4. Experimental Results and Analysis
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Wu Peng [ College of Mechanical and Electronic Engineering, Northeast Forestry University, Harbin 150040 China ]
• Xu Hongling [ College of Mechanical and Electronic Engineering, Northeast Forestry University, Harbin 150040 China ]
• Li Wenlin [ College of Mechanical and Electronic Engineering, Northeast Forestry University, Harbin 150040 China ]
• Song Wenlong [ College of Mechanical and Electronic Engineering, Northeast Forestry University, Harbin 150040 China ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605