An efficient image matching method using Speed Up Robust Features

Author

Baofeng Zhang ; Yingkui Jiao ; Zhijun Ma ; Yongchen Li ; Junchao Zhu

Author_Institution

Tianjin Key Lab. for Control Theor. & Applic. in Complicated Syst., Tianjin Univ. of Technol., Tianjin, China

fYear

2014

fDate

3-6 Aug. 2014

Firstpage

553

Lastpage

558

Abstract

The kernel of stereo vision system is stereo matching. In this paper proposed, an efficient image matching algorithm based on Speed Up Robust Features (SURF). Compared with traditional methods, this approach has enormous advantages of less computations and short time-consuming. The approach uses SURF algorithm to extract feature points. The feature descriptor of the approach is determined by Haar wavelet. The RANdom SAmple Consensus (RANSAC) algorithm is used to eliminate the false matches and wrong match point. The experimental results show that the approach is robust and has fast matching speed. That makes an important application field of 3D reconstruction.

Keywords

Haar transforms; feature extraction; image matching; stereo image processing; 3D reconstruction; Haar wavelet; RANSAC algorithm; SURF; efficient image matching method; feature descriptor; feature points extraction; random sample consensus; speed up robust features; stereo matching; stereo vision system; Algorithm design and analysis; Feature extraction; Filtering theory; Image matching; Robustness; Stereo vision; Three-dimensional displays; Feature point; Image matching; RANdom SAmple Consensus (RANSAC); Speed Up Robust Features (SURF);

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronics and Automation (ICMA), 2014 IEEE International Conference on

Conference_Location

Tianjin

Print_ISBN

978-1-4799-3978-7

Type

conf

DOI

10.1109/ICMA.2014.6885757

Filename

6885757