The detection and classification of faults is a major task for optical non-destructive testing in industrial quality control. Interferometric fringes contain a large amount of image data with information about possible defect structures. This mass of data must be reduced for further evaluation. One possible way is the filtering of these images applying the adaptive wavelet transform. The extraction and classification of disturbances in interferometric fringe patterns, the application of several wavelet functions with different parameters for the detection of faults, and the combination of wavelet filters for fault classification was already shown in [7-9]. Especially in [9] we suggested a simple algorithm for classifying the fringe pattern. In this paper we concentrate on the detection of the bend and compression class. With synthetically created ideal bend and compression fringe patterns we had the ability to test the resolution of our system and to find the best wavelet filters for these fault classes.
展开▼
