A 2-dimensional Wavelet based approach to recognise defects in C-scan maps

An image processing procedure is proposed to detect porosity defects in composite materials, analyzing C-scan images obtained by ultrasound inspection techniques. An image described by a set of features is analyzed in order to evaluate its similarity with a reference set. A 2D wavelet transform is applied to the input image and then a feature extraction based on statistics of the detail images produced by the transform itself is performed. The Principal Component Analysis technique (PCA) is then applied in order to map input features into an output plane maximizing data variance. Finally the image is classified considering the distance between points in the PCA plane. This procedure is also applied for the analysis of a single image. Preliminary results on simulation images and real C-scan maps, show that the procedure is able to detect defects.