Application-based approach for automatic texture defect recognition on synthetic surfaces

Synthetic surfaces, in particular polymer structures, which are used for electronic components, have to be inspected in industrial processes. Polymers show some specific surface characteristics. This a-priori knowledge is useable for the feature extraction of a surface texture and a following classification. The feature extraction is performed by using statistical information, calculated from sum and difference histograms, while the classification is executed by a fuzzy pattern classifier. A defect area can be recognized just on the basis of the tested image and without the need of any further reference learning data. The classification of a defect part is achieved by analyzing the divergence of the extracted feature values from their median related to the inspected area. Surfaces that contain an inconsistent texture will be rejected.