Non-Rigid Registration via Global to Local Transformation

Autor: Hao Pan, Yi Ma, Fangrong Zhou, Yan Gu, Yutang Ma, Chaobo Min
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Tehnički Vjesnik, Vol 27, Iss 1, Pp 174-183 (2020)
Druh dokumentu: article
ISSN: 1330-3651
1848-6339
20190913
DOI: 10.17559/TV-20190913061345
Popis: 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.
Databáze: Directory of Open Access Journals