Journal of Systems Engineering and Electronics ›› 2009, Vol. 20 ›› Issue (1): 50-54.

• ELECTRONICS TECHNOLOGY • Previous Articles     Next Articles

Scale invariant features extraction for stereo vision

Liu Li1,2, Peng Fuyuan1, Tian Yan1 & Wan Yaping2   

  1. 1. Dept. of Telecommunication, Huazhong Science and Technology Univ., Wuhan 430074, P. R. China;
    2. Dept. of Computer Science and Technology, Nanhua Univ., Hengyang 421001, P. R. China
  • Online:2009-02-18 Published:2010-01-03

Abstract:

Stable local feature detection is a fundamental component of many stereo vision problems such as 3-D reconstruction, object localization, and object tracking. A robust method for extracting scale-invariant feature points is presented. First, the Harris corners in three-level pyramid are extracted. Then, the points detected at the highest level of the pyramid are correctly propagated to the lower level by pyramid based scale invariant (PBSI) method. The corners detected repeatedly in different levels are chosen as final feature points. Finally, the characteristic scale is obtained based on maximum entropy method. The experimental results show that the algorithm has low computation cost, strong antinoise capability, and excellent performance in the presence of significant scale changes.