Gradual-SURF

Author

Huang, Xiangsheng ; Wang, Jie ; Zhang, Mandun ; Zhai, Jun

Author_Institution

Inst. of Autom., Beijing, China

Volume

2

fYear

2011

fDate

15-17 Oct. 2011

Firstpage

906

Lastpage

909

Abstract

In order to improve the high complexity problem of SIFT, SURF algorithm uses the DoH (Determinant of the Hessian) which is simplified and approximate. This improvement not only guarantees the stability of the algorithm, but also increases the calculation efficiency. But when the SURF simplifies the DoH gaussian second order differential template, some of the image gradient information were lost. Therefore, an Gradual SURF(G-SURF) operator is proposed in the this paper, and the gradient information is added in the process. Experimental results show that the proposed improved SURF operator can get a more stable effect, and improve calculation complexity at the same time.

Keywords

Gaussian processes; computational complexity; edge detection; gradient methods; image matching; DoH gaussian second order differential template; G-SURF operator; Gradual-SURF algorithm; SIFT problem; algorithm stability; calculation complexity; corner detection; determinant of the Hessian; image gradient information; stereo matching; Algorithm design and analysis; Approximation algorithms; Feature extraction; Filtering algorithms; Robustness; Stability analysis; Vectors; Corner detection; SIFT; SURF; Stereo matching;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing (CISP), 2011 4th International Congress on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-9304-3

Type

conf

DOI

10.1109/CISP.2011.6100375

Filename

6100375