Optical feature extraction with illumination-encoded linear functions
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Philip R. Bingham, Edmund Y. Lam (Hrsg.), Image Processing: Machine Vision Applications V, Proc. SPIE, Bd. 8300, 2012.
Electronic Imaging: Image Processing: Machine Vision Applications V, Burlingame, California, USA, 22.-26. Januar 2012
The choice of an appropriate illumination design is one of the most important steps in creating successful machine vision systems for automated inspection tasks. In a popular technique, multiple inspection images are captured under angular-varying illumination directions over the hemisphere, which yields a set of images referred to as illumination series. However, most existing approaches are restricted in that they use rather simple patterns like point- or sector-shaped illumination patterns on the hemisphere. In this paper, we present an illumination technique which reduces the effort for capturing inspection images for each reflectance feature by using linear combinations of basis light patterns over the hemisphere as feature-specific illumination patterns. The key idea is to encode linear functions for feature extraction as angular-dependent illumination patterns, and thereby to compute linear features from the scene's reflectance field directly in the optical domain. In the experimental part, we evaluate the proposed illumination technique on the problem of optical material type classification of printed circuit boards (PCBs).