Earticle

초록

영어

Classic SURF algorithm may lead to matching failure, low recall because of incorrect main direction when constructing feature points describing operator. To solve it, A Method using auxiliary direction to improve SURF recall is put forward. The improved algorithm first select out auxiliary direction which is similar to main direction in characteristics, then generate new operator for describing the auxiliary direction characteristic. When matching, the improved algorithm adopts stricter nearest neighbor proportion inhibition. Experimental results show that feature point recall increase about 6% compared with the classical SURF while maintaining the precision.

목차

Abstract
 1. Introduction
 2. Detecting and Matching Feature Points in SURF
  2.1 Constructing Scale Space
  2.2 Determining Feature Points
  2.3 Distributing Principal Direction
  2.4 Generating Descriptor
  2.5 Matching Feature Points
  2.6 The Performance Index of Algorithm
 3. Using Auxiliary Direction to Improve SURF Algorithm
  3.1 The Reason of Introducing Auxiliary Direction
  3.2 The Method of Introducing Auxiliary Direction
  3.3 The Preliminary Effect of Introducing Auxiliary Direction
  3.4 The Changes of Matching Inhibition Policy
  3.5 The Flow Diagram of the Improvement
 4. The Result and the Analysis of the Experiment
  4.1. Experimental Parameters Setting
  4.2. Contrast Experiment
  4.3 Analysis of Experimental Results
 5. Conclusions
 References

키워드

저자

• Linhua Zhang [ Computer Engineering Department, Taiyuan Institute of Technology, Taiyuan, 030008 China ]
• Xiaodong Yue [ Computer Engineering and Science College, Shanghai University, Shanghai, 200444 China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605