An Algorithm of Image Matching Based on Mahalanobis Distance and Weighted KNN Graph

Author

Du Bo ; Zhangguan-liang ; Cuixiao-long

Author_Institution

Urumqi Command Coll. of CAPF, Urumqi, China

fYear

2015

fDate

24-26 April 2015

Firstpage

116

Lastpage

121

Abstract

A point pattern matching algorithm based on Mahalanobis distance is proposed, which effect is analyzed and confirmed by experiments. Secondly, the Graph Transformation Matching algorithm and Weighted Graph Transformation Matching algorithm are studied deeply. To overcome the limitation of Mahalanobis distance and WGTM, a novel and robust point pattern matching algorithm based on Weighted Graph Transformation using Mahalanobis distance is proposed. The similarity evaluated by Mahalanobis distance is embedded into WGTM algorithm under the constraint of median distance and angular distance. Then point pairs were obtained through iteratively eliminating the outliers. Experimental results on synthetic data and real-world data demonstrate that the proposed algorithm is effective and robust.

Keywords

graph theory; image matching; Mahalanobis distance; WGTM algorithm; angular distance constraint; image matching; iterative outlier elimination; median distance constraint; point pattern matching algorithm; real-world data; similarity evaluated; synthetic data; weighted KNN graph; weighted graph transformation matching algorithm; Accuracy; Data models; Image matching; Image registration; Noise; Vibrations; Image matching; KNN Graph; Mahalanobis Distance; angular distance;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science and Control Engineering (ICISCE), 2015 2nd International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4673-6849-0

Type

conf

DOI

10.1109/ICISCE.2015.34

Filename

7120574