Authors:
Faisal Azhar
1
;
Khemraj Emrith
2
;
Stephen Pollard
1
;
Melvyn Smith
2
;
Guy Adams
1
and
Steve Simske
1
Affiliations:
1
Hewlett Packard Laboratories, United Kingdom
;
2
University of West of England, United Kingdom
Keyword(s):
Micro-scale Photometric Stereo, Lambert Reflectance Model, Paper and Surface Normals.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Document Imaging in Business
;
Features Extraction
;
Geometry and Modeling
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Image Formation, Acquisition Devices and Sensors
;
Image Registration
;
Image-Based Modeling
;
Pattern Recognition
;
Software Engineering
Abstract:
This paper presents an empirical study to investigate the use of photometric stereo (PS) for micro-scale 3D measurement of paper samples. PS estimates per-pixel surface orientation from images of a surface captured from the same viewpoint but under different illumination directions. Specifically, we investigate the surface properties of paper to test whether they are sufficiently well approximated by a Lambertian reflectance model to allow veridical surface reconstruction under PS and explore the range of conditions for which this model is valid. We present an empirical setup that is used to conduct a series of experiments in order to analyse the applicability of PS at the micro-scale. In addition, we determine the best 4, 6, and 8 light source tilt (illumination) angles with respect to multi-source micro-scale PS. Furthermore, an intensity based image registration method is used to test the accuracy of the recovery of surface normals. The results demonstrate that at the micro-scale:
(a) Lambert model represents well the data sets with low root mean square (RMS) error between the original and reconstructed image, (b) increasing the light sources from 4 to 8 reduces
RMS error, and (c) PS can be used to extract veridical surface normals.
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