New approach to defect detection for NDT applications by using topological derivative

Image segmentation is one of the most challenging problems in non-destructive testing (NDT) for industrial quality control where digitized radiographs or X-ray computerized tomography images are usually concerned in. The topological derivative based segmentation algorithms can be do well in these images with low signal to noise and contrast to noise ratio but the results are heavily affected by the image homogeneity and election of cost function. Note that the defects in these images usually lie in a very small area. An expensive computational cost with undesired result would be gained if segmenting were done on the whole image domain. Therefore a new strategy in this paper is proposed to remedy this problem. First the image is roughly segmented into a set of regions using pyramid linking. Then the scale parameters of cost function are computed for every sub region based on properties of the region. Finally, refinement can be performed on the sub regions using topological derivative method. The proposed algorithm has been demonstrated by several cases.