Open AccessValid point detection in fringe projection profilometry
Author(s) -
Haixia Wang,
Qian Kemao,
Seah Hock Soon
Publication year - 2015
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.23.007535
Subject(s) - computer science , segmentation , artificial intelligence , point (geometry) , projection (relational algebra) , computer vision , profilometer , cluster analysis , object detection , noise (video) , image processing , point spread function , structured light 3d scanner , optics , algorithm , image (mathematics) , mathematics , physics , geometry , scanner , quantum mechanics , surface roughness
Fringe projection profilometry has become one of the most popular 3D information acquisition techniques being developed over the past three decades. However, the general and practical issues on valid point detection, including object segmentation, error correction and noisy point removal, have not been studied thoroughly. Furthermore, existing valid point detection techniques require multiple case-dependent thresholds which increase processing inconvenience. In this paper, we proposed a new valid point detection framework, which includes the k-means clustering for automatic background segmentation, unwrapping error correction based on theoretical analysis, and noisy point detection in both temporal and spatial directions with automatic threshold setting. Experimental results are given to validate the proposed framework.