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Research Article | Open Access

Photometric stereo for strong specular highlights

Chair of Applied Mathematics, Brandenburg University of Technology, Cottbus 03046, Germany.
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Abstract

Photometric stereo is a fundamental technique in computer vision known to produce 3D shape with high accuracy. It uses several input images of a static scene taken from one and the same camera position but under varying illumination. The vast majority of studies in this 3D reconstruction method assume orthographic projection for the camera model. In addition, they mainly use the Lambertian reflectance model as the way that light scatters at surfaces. Thus, providing reliable photometric stereo results from real world objects still remains a challenging task. We address 3D reconstruction by use of a more realistic set of assumptions, combining for the first time the complete Blinn–Phong reflectance model and perspective projection. Furthermore, we compare two different methods of incorporating the perspective projection into our model. Experiments are performed on both synthetic and real world images; the latter do not benefit from laboratory conditions. The results show the high potential of our method even for complex real world applications such as medical endoscopy images which may include many specular highlights.

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Computational Visual Media
Pages 83-102

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Cite this article:
Khanian M, Boroujerdi AS, Breuß M. Photometric stereo for strong specular highlights. Computational Visual Media, 2018, 4(1): 83-102. https://doi.org/10.1007/s41095-017-0101-9

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Revised: 04 September 2017
Accepted: 01 December 2017
Published: 14 February 2018
© The Author(s) 2017

This article is published with open access at Springerlink.com

The articles published in this journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Other papers from this open access journal are available free of charge from http://www.springer.com/journal/41095. To submit a manuscript, please go to https://www. editorialmanager.com/cvmj.