Title: Assessment of the Influence of Adaptive Components in Trainable Surface Inspection Systems
Authors: Eitzinger, Christian * ×
Heidl, Wolfgang *
Lughofer, Edwin *
Raiser, Stefan *
Smith, Jim *
Tahir, Muhammad Atif *
Sannen, Davy *
Van Brussel, Hendrik * #
Issue Date: Jul-2009
Publisher: Springer International
Series Title: Machine vision and applications issue:Special Issue
Abstract: In this paper we present a framework for the classification of images in surface inspection tasks and address several key aspects of the processing chain from the original image to the final classification result. A major contribution of this paper is a quantitative assessment of how incorporating adaptivity into the feature calculation, the feature pre-processing, and into the classifiers themselves, influences the final image classification performance. Hereby, results achieved on a range of artificial and real-world test data from applications in printing, die-casting, metal processing and food production are presented.
ISSN: 0932-8092
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Production Engineering, Machine Design and Automation (PMA) Section
* (joint) first author
× corresponding author
# (joint) last author

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