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Proceedings Paper

Multi-modal image registration via depth information based on point set matching
Author(s): Bin Sun; Qi Yang; Kai Hu; Honglin Bai
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Paper Abstract

Image registration is an important pre-processing operation to perform multi-modal joint analysis correctly. However, registration of images captured by different sensors is a very challenging problem due to the apparent differences of scenes. Traditional Coherent Point Drift method (CPD) is a global registration approach, which strongly relies on the extracted features. In the case of infrared and visible images, registration methods based on edges or points are inappropriate since those features might be significantly different. Fortunately, depth information is more robust feature for multi-modal image pairs. In this paper, we propose an algorithm based on Canny to extract edge of objects. And the regions of interest (ROI) is obtained by depth maps of image pairs in which common features usually successfully implemented by point set registration. Experimental results on real world data demonstrate the effectiveness of the proposed approach, which is superior to the traditional CPD algorithm for multi-modal image registration.

Paper Details

Date Published: 8 March 2018
PDF: 8 pages
Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 106090J (8 March 2018); doi: 10.1117/12.2284119
Show Author Affiliations
Bin Sun, Univ. of Electronic Science and Technology of China (China)
Qi Yang, Univ. of Electronic Science and Technology of China (China)
Kai Hu, Univ. of Electronic Science and Technology of China (China)
Honglin Bai, Univ. of Electronic Science and Technology of China (China)


Published in SPIE Proceedings Vol. 10609:
MIPPR 2017: Pattern Recognition and Computer Vision
Zhiguo Cao; Yuehuang Wang; Chao Cai, Editor(s)

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