A novel image matching algorithm based on PCA and SIFT. (November 2020)

• Record Type: Journal Article
• Authors: Li, Wenju; Na, Xinyuan; Su, Pan; Lu, Yunfan; Dong, Tianzhen
• Is Part Of: Journal of physics. Volume 1684(2020)
• Publication Date: 2020-11
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1684/1/012099
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In order to solve the problem of low matching precision and slow matching speed of image matching algorithm based on classical SIFT, a new image matching algorithm based on PCA, SIFT and improved RANSAC is proposed. Firstly, the SIFT feature was extracted from images; Secondly, principal component analysis is used to reduce the dimension of SIFT feature descriptor, from 128 to 20; then, the EUCLIDEAN distance is used for feature matching; finally, an improved RANSAC algorithm is proposed to eliminate the mismatched feature points. Experimental results show that the proposed algorithm improves the accuracy and speed of image matching.