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Technical gazette, Vol. 27 No. 1, 2020.

Original scientific paper

https://doi.org/10.17559/TV-20190913061345

Non-Rigid Registration via Global to Local Transformation

Hao Pan* ; Electrical Research Institute of Yunnan Electric Power Research Institute, (Group) Co., Ltd. Kunming, 650051, China
Yi Ma ; Electrical Research Institute of Yunnan Electric Power Research Institute, (Group) Co., Ltd. Kunming, 650051, China
Fangrong Zhou ; Electrical Research Institute of Yunnan Electric Power Research Institute, (Group) Co., Ltd. Kunming, 650051, China
Yan Gu ; North Night Vision Technology Corp., Ltd. Nanjing, 211102, China
Yutang Ma ; Electrical Research Institute of Yunnan Electric Power Research Institute, (Group) Co., Ltd. Kunming, 650051, China
Chaobo Min ; North Night Vision Technology Corp., Ltd. Nanjing, 211102, China

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Abstract

Non-rigid point set and image registration are key problems in plenty of computer vision and pattern recognition tasks. Typically, the non-rigid registration can be formulated as an optimization problem. However, registration accuracy is limited by local optimum. To solve this problem, we propose a method with global to local transformation for non-rigid point sets registration and it also can be used to infrared (IR) and visible (VIS) image registration. Firstly, an objective function based on Gaussian fields is designed to make a problem of non-rigid registration transform into an optimization problem. A global transformation model, which can describe the regular pattern of non-linear deformation between point sets, is then proposed to achieve coarse registration in global scale. Finally, with the results of coarse registration as initial value, a local transformation model is employed to implement fine registration by using local feature. Meanwhile, the optimal global and local transformation models estimated from edge points of IR and VIS image pairs are used to achieve non-rigid image registration. The qualitative and quantitative comparisons demonstrate that the proposed method has good performance under various types of distortions. Moreover, our method can also produce accurate results of IR and VIS image registration.

Keywords

Gaussian fields; global transformation; infrared image; non-rigid transformation; registration

Hrčak ID:

234213

URI

https://hrcak.srce.hr/234213

Publication date:

15.2.2020.

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