PCB CT Image Segmentation Based on Level Set with Shape Prior

It is a new method to nondestructively test PCB using CT in recent years. However, because of a lot of mental components in PCB, there will be serious metal artifacts, which results in the images with intensity inhomogeneity. Aiming at this problem, a novel level set method based on shape prior is proposed. Firstly, PCB CT image is filtered by different orientation Gabor filters according to the obvious orientation feature of lines in PCB. The edge-enhanced result can be obtained by weighted sum of different orientation filtered results and the background noise of edge-enhanced image can be weakened by localization method. The shape prior can be obtained after using threshold and morphological closing operation. Then, the energy function consists of Chan-Vese item, localized energy item and shape prior item which is represented by probabilistic definition of shape. Finally, the segmentation result can be obtained by minimizing the energy function. The experiments of PCB CT images with multi-object and intensity inhomogeneity demonstrate the performance of our model.