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Title: Inpainting for fringe projection profilometry based on geometrically guided iterative regularization
Authors: Budianto
Lun, DPK 
Issue Date: 2015
Source: IEEE transactions on image processing, 2015, v. 24, no. 12, 7274711, p. 5531-5542
Abstract: Conventional fringe projection profilometry methods often have difficulty in reconstructing the 3D model of objects when the fringe images have the so-called highlight regions due to strong illumination from nearby light sources. Within a highlight region, the fringe pattern is often overwhelmed by the strong reflected light. Thus, the 3D information of the object, which is originally embedded in the fringe pattern, can no longer be retrieved. In this paper, a novel inpainting algorithm is proposed to restore the fringe images in the presence of highlights. The proposed method first detects the highlight regions based on a Gaussian mixture model. Then, a geometric sketch of the missing fringes is made and used as the initial guess of an iterative regularization procedure for regenerating the missing fringes. The simulation and experimental results show that the proposed algorithm can accurately reconstruct the 3D model of objects even when their fringe images have large highlight regions. It significantly outperforms the traditional approaches in both quantitative and qualitative evaluations.
Keywords: 3D model reconstruction
Fringe projection profilometry
Image inpainting
Iterative regularization
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE transactions on image processing 
ISSN: 1057-7149
EISSN: 1941-0042
DOI: 10.1109/TIP.2015.2481707
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