Research of shoeprint image matching based on SIFT algorithm

Article type: Research Article

Authors: Wang, Hongxing^* | Fan, Jihui | Li, Yan

Affiliations: School of Mechanical & Power Engineering, Henan Polytechnic University, Jiaozuo, Henan, China

Correspondence: [*] Corresponding author: Hongxing Wang, School of Mechanical & Power Engineering, Henan Polytechnic University, Jiaozuo, Henan, China. E-mail:[email protected]

Abstract: It researches on shoeprint image positioning and matching. Firstly, this paper introduces the algorithm of Scale-invariant feature transform (SIFT) into shoeprint matching. Then it proposes an improved matching algorithm of SIFT. Because of its good scale and illumination invariant, the algorithm can be used to go on the shoeprint matching. The secondary positioning on the image will be used before the feature points are created. It makes shoeprint image in the same vertical position. After that, use the minimum Euclidean distance as the standard of shoeprint matching. According to the ratio of the minimum Euclidean distance to the second minimum Euclidean distance, the invalid points are removed. That can improve the matching efficiency. The results of experiment show that the algorithm can not only shorten the matching time, but also improve the matching accuracy with high robust.

Keywords: Image matching, SIFT, secondary positioning, shoeprint

DOI: 10.3233/JCM-160622

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 16, no. 2, pp. 349-359, 2016