Assessment of the Influence of Adaptive Components in Trainable Surface Inspection Systems
Sprache des Titels:
Englisch
Original Kurzfassung:
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.