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Proceedings Paper

Miniature photometric stereo system for textile surface structure reconstruction
Author(s): Dimitris Gorpas; Christos Kampouris; Sotiris Malassiotis
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Paper Abstract

In this work a miniature photometric stereo system is presented, targeting the three-dimensional structural reconstruction of various fabric types. This is a supportive module to a robot system, attempting to solve the well known “laundry problem”. The miniature device has been designed for mounting onto the robot gripper. It is composed of a low-cost off-the-shelf camera, operating in macro mode, and eight light emitting diodes. The synchronization between image acquisition and lighting direction is controlled by an Arduino Nano board and software triggering. The ambient light has been addressed by a cylindrical enclosure. The direction of illumination is recovered by locating the reflection or the brightest point on a mirror sphere, while a flatfielding process compensates for the non-uniform illumination. For the evaluation of this prototype, the classical photometric stereo methodology has been used. The preliminary results on a large number of textiles are very promising for the successful integration of the miniature module to the robot system. The required interaction with the robot is implemented through the estimation of the Brenner’s focus measure. This metric successfully assesses the focus quality with reduced time requirements in comparison to other well accepted focus metrics. Besides the targeting application, the small size of the developed system makes it a very promising candidate for applications with space restrictions, like the quality control in industrial production lines or object recognition based on structural information and in applications where easiness in operation and light-weight are required, like those in the Biomedical field, and especially in dermatology.

Paper Details

Date Published: 24 May 2013
PDF: 12 pages
Proc. SPIE 8791, Videometrics, Range Imaging, and Applications XII; and Automated Visual Inspection, 879117 (24 May 2013); doi: 10.1117/12.2018913
Show Author Affiliations
Dimitris Gorpas, Ctr. for Research and Technology Hellas (Greece)
Univ. of California, Davis (United States)
Christos Kampouris, Ctr. for Research and Technology Hellas (Greece)
Sotiris Malassiotis, Ctr. for Research and Technology Hellas (Greece)


Published in SPIE Proceedings Vol. 8791:
Videometrics, Range Imaging, and Applications XII; and Automated Visual Inspection
Fabio Remondino; Jürgen Beyerer; Fernando Puente León; Mark R. Shortis, Editor(s)

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