Contour-Based Image Registration using Bipartite Graph Matching with Munkres Algorithm

Authors

Qingsong Zhu, Key Lab for Health Informatics, Chinese Academy of Sciences, Shenzhen 518055, China\\ Shenzhen Key Lab for Low-Cost Healthcare, Chinese Academy of Sciences, Shenzhen 518055, China\\ Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China\\ School of Medicine, Stanford University, Stanford, California, USA
Tiexiang Wen
Yaoqin Xie
Jia Gu
Lei Wang

Author Country (or Countries)

USA

Abstract

Image registration is a vital research topic in image processing. In this paper, we present a novel method to register color image and depth information captured by Kinect for Xbox 360. A contour-based approach is employed to find the correspondence points and estimate the transformation parameters model between color image and depth image. In our paper, the boundary contours are detected by Canny edge detector and located to sub-pixel level by a B-spline model. The shape descriptors of contours are computed by shape context. The correspondence points on both similar contours will have similar shape descriptors, which enables us to solve a bipartite graph matching with Munkres algorithm. Based on the correspondence points, the transform model that best aligns the two images can be estimated via RANSAC method. Experiments on a series of natural images are used for compare with some existing approaches and demonstrate the effectiveness of our method.

Suggested Reviewers

N/A

Digital Object Identifier (DOI)

http://dx.doi.org/10.18576/amis/080132

Recommended Citation

Zhu, Qingsong; Wen, Tiexiang; Xie, Yaoqin; Gu, Jia; and Wang, Lei (2014) "Contour-Based Image Registration using Bipartite Graph Matching with Munkres Algorithm," Applied Mathematics & Information Sciences: Vol. 08: Iss. 1, Article 32.
DOI: http://dx.doi.org/10.18576/amis/080132
Available at: https://digitalcommons.aaru.edu.jo/amis/vol08/iss1/32