Title :
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
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;
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
DOI :
10.1109/CISP.2009.5304375
