Improved Harris algorithm within scale-invariance

Author

Yongtao, Hao ; Ping, Yu

Author_Institution

CAD Res. Center, Tongji Univ., Shanghai, China

fYear

2010

fDate

Nov. 30 2010-Dec. 2 2010

Firstpage

671

Lastpage

675

Abstract

Based on the SIFT recognition method, this solution is to obtain the natural features in computer vision recognition and matching by means of the Gauss pyramid, DOG pyramid, their differential functions appoximated instead of σ²∇²G to achieve the scale invariance practice. Through the Harris corner detection algorithm for the corresponding transformation formula, and the Gauss pyramids, DOG pyramid, the modified algorithm obtain a certain degree of scale invariance. This improved algorithm can be used either to supplement characteristics of the SIFT algorithm, and can also be used as a separately kind of scale invariance of the feature recognition algorithm.

Keywords

Gaussian processes; differential equations; edge detection; feature extraction; DOG pyramid; Gauss pyramid; Harris corner detection algorithm; SIFT recognition method; computer vision recognition; differential functions; feature recognition; DOG pyramid; Feature recognition; Gaussian pyramid; Harris corner detection; scale invariance; sift;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Sciences and Convergence Information Technology (ICCIT), 2010 5th International Conference on

Conference_Location

Seoul

Print_ISBN

978-1-4244-8567-3

Electronic_ISBN

978-89-88678-30-5

Type

conf

DOI

10.1109/ICCIT.2010.5711139

Filename

5711139