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  4. Optical feature extraction with illumination-encoded linear functions
 
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2012
Conference Paper
Title

Optical feature extraction with illumination-encoded linear functions

Abstract
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).
Author(s)
Gruna, Robin  
Beyerer, Jürgen  
Mainwork
Image processing: Machine vision applications V  
Conference
Conference "Image Processing - Machine Vision Applications" 2012  
Open Access
File(s)
Download (4.27 MB)
Rights
Use according to copyright law
DOI
10.24406/publica-r-375673
10.1117/12.907409
Language
English
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Keyword(s)
  • KCM

  • optical feature extraction

  • hemispherical illumination functions

  • reflectance fields

  • illumination series

  • material classification

  • multivariate image analysis

  • automated visual inspection

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