Partially overlapped range images registration based on fringe pattern profilometry

Registration of two three-dimensional (3-D) point sets is a fundamental problem of 3-D shape measurement and modeling pipeline. This paper investigates the automatic pair-wise method to register partially overlapped range images generated by self-developed fringe pattern profilometry (FPP) system. The method is based on the classic iterative closest point (ICP) algorithm but combined with several extensions to adapt to the experimental data. Firstly, the distance function for correspondence finding is modified to be the weighted linear combination of positions and Euclidean invariant features for improving the probability of convergence. In addition, outliers can be discarded through robust statistics and adaptive thresholding of weighted distances between corresponding point pairs. Both artificial and real data are used to test the proposed method. In the ideal noise-free conditions, the experimental results illustrate that it converges to the global minima. The experimental results also show that the proposed method increases the possibility of global convergence when deal with partially overlapped range images.