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

机译:基于对象图像边缘检测的基于对象图像边缘检测的快速质量引导相展示算法

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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.
机译:与三维条纹图案轮廓测定法(3D-FPP)系统相关的主要挑战是从复杂物体表面形状具有鲁棒性和速度保证的相相映射的展开。在本文中,我们提出了一种新的质量引导相展示算法。与传统的质量导向方法相比,我们通过检测对象图像上的边缘像素来分为两种类型的像素:对应于平滑相位变化和低质量(LQ)粗相变的高质量(HQ)像素。为了提高计算效率,通过不同的方法揭开这两种类型的像素。也就是说,HQ像素由算法之后的简单路径未包装,并且通过传统的洪水填充算法恢复LQ。实验表明,该方法能够将复杂的相位映射解开与与传统质量引导算法相似的准确性性能和更高的速度。

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