Segmentation of welding discontinuities using a robust algorithm

This work presents a new method capable of segmenting welding discontinuities using robust digital image processing techniques, which include noise attenuation filters, morphological mathematical operators and edge detection techniques such as the canny filter, the watershed transform and the distance transform. In order to determine the quality of the segmentation generated by the algorithm, the segmented image is compared with an ideal binary image developed manually. The results of this study have led to the development of the following scheme: first a median filter is used for noise reduction; second, a bottom hat filter is used to separate hypothetical discontinuities from their background; third, the segmented regions are identified by means of binary thresholding; fourth, filters taken from morphological mathematics are used to eliminate oversegmentation; and fifth, the watershed transform is used to separate internal regions. The results of the study have generated an area underneath the receiver operation characteristic curve of 0.9358 in a set of ten images. The best operational point reached corresponds to an 87.83% sensitivity and a 9.40% of 1-specificity.