A Method of Improving SIFT Algorithm Matching Efficiency

Author

Zhu, Daixian ; Wang, Xiaohua

Author_Institution

Commun. & Inf. Eng. Coll., Xi´´an Univ. of Sci. & Technol., Xi´´an, China

fYear

2009

fDate

17-19 Oct. 2009

Firstpage

1

Lastpage

5

Abstract

Due to the good invariance of scale, rotation, illumination, SIFT (scale invariant feature transform) descriptor is commonly used in image matching, but its algorithm is complicated and computation time is long. To improve SIFT feature matching algorithm efficiency, the method of reducing similar measure matching cost is mentioned. Euclidean distance is replaced by the linear-combination of city block distance and chessboard distance, and reduce character point in calculating with results of part feature. The experimental results show that the algorithm can reduce the rate of time complexity and maintain robust quality at the same time, image matching efficiency is improved.

Keywords

computational complexity; cost reduction; feature extraction; image matching; transforms; Euclidean distance; chessboard distance; city block distance; feature extraction; feature matching algorithm efficiency; image matching; scale invariant feature transform descriptor; similar measure matching cost reduction; time complexity; Computer vision; Costs; Data mining; Educational institutions; Euclidean distance; Feature extraction; Image matching; Lighting; Pixel; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Signal Processing, 2009. CISP '09. 2nd International Congress on

Conference_Location

Tianjin

Print_ISBN

978-1-4244-4129-7

Electronic_ISBN

978-1-4244-4131-0

Type

conf

DOI

10.1109/CISP.2009.5304375

Filename

5304375