Fast quality-guided phase unwrapping algorithm for 3D profilometry based on object image edge detection

Abstract

A main challenge associated with 3-dimentional fringe pattern profilometry (3D-FPP) systems is the unwrapping of phase maps resulted from complex object surface shapes with both robustness and speed guaranteed. In this paper we propose a new quality-guided phase unwrapping algorithm. In contrast to the conventional quality-guided methods, we classify pixels on wrapped phase map into two types by detecting edge pixels on object image: high quality (HQ) pixels corresponding to smooth phase changes and low quality (LQ) ones to rough phase changes. In order to improve the computational efficiency, these two types of pixels are unwrapped by means of different approaches. That is, the HQ pixels are unwrapped by a simple path following algorithm and the LQ ones are recovered by conventional flood-fill algorithm. Experiments show that the proposed approach is able to unwrap complex phase maps with the similar accuracy performance as and much higher speed than the conventional quality-guided algorithm.