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A composite quality-guided phase unwrapping algorithm for fast 3D profile measurement

机译:用于快速3D轮廓测量的复合质量引导相位展开算法

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摘要

Fringe pattern profilometry (FPP) is one of the most promising 3D profile measurement techniques, which has been widely applied in many areas. A challenge problem associated with FPP is the unwrapping of wrapped phase maps resulted from complex object surface shapes. Although existing quality-guided phase unwrapping algorithms are able to solve such a problem, they are usually extensively computational expensive and not able to be applied to fast 3D measurement scenarios. This paper proposes a new quality-guided phase unwrapping algorithm with higher computational efficiency than the conventional ones. In the proposed method, a threshold of quality value is used to classify pixels on the phase maps into two types: high quality (HQ) pixels corresponding to smooth phase changes and low quality (LQ) ones to rough phase variance. In order to improve the computational efficiency, the HQ pixels are unwrapped by a computationally efficient fast phase unwrapping algorithm, and the LQ pixels are unwrapped by computational expensive flood-fill algorithm. Experiments show that the proposed approach is able to recover complex phase maps with the similar accuracy performance as the conventional quality-guided phase unwrapping algorithm but is much faster than the later. © 2012 SPIE.
机译:条纹图案轮廓测量(FPP)是最有前途的3D轮廓测量技术之一,已广泛应用于许多领域。与FPP相关的挑战性问题是由复杂物体表面形状导致的包裹相图的展开。尽管现有的质量指导相位展开算法能够解决此类问题,但它们通常在计算上非常昂贵,并且无法应用于快速3D测量场景。提出了一种新的质量导引相位解缠算法,具有比传统算法更高的计算效率。在所提出的方法中,使用质量值的阈值将相位图上的像素分为两种类型:对应于平滑相位变化的高质量(HQ)像素和对应于粗糙相位方差的低质量(LQ)像素。为了提高计算效率,通过计算有效的快速相位解包算法来解包HQ像素,并且通过计算上昂贵的泛洪算法来解包LQ像素。实验表明,该方法能够恢复复杂的相位图,并具有与传统的质量指导相位展开算法相似的准确度性能,但比后一种方法要快得多。 ©2012 SPIE。

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