An image content description technique for the inspection of Specular objects

Abstract

This paper proposed an image content description method within the context of specular surface inspection. Such a method is based on a preliminary research concerning the generation of specific stripe patterns for the visual enhancement of defective surface parts of cylindrical specular objects. The goal of this paper is to address the stripe pattern interpretation within a general approach. For this purpose, different pattern recognition processes, consisting not only of the combination of different image segmentation, feature retrieval, and classification, but also of feature combination and selection, will be considered. Three top-down and one bottom-up approaches are evaluated for retrieving the most appropriate feature sets in terms of highest classification rates. It will be demonstrated that following a combination and appropriate selection of these feature sets, even better rates can be reached. With only half of the initial features, an increase of more than 2% is observable.