An efficient similarity measure approach for PCB surface defect detection

In this paper, an efficient similarity measure method is proposed for printed circuit board (PCB) surface defect detection. The advantage of the presented approach is that the measurement of similarity between the scene image and the reference image of PCB surface is taken without computing image features such as eigenvalues and eigenvectors. In the proposed approach, a symmetric matrix is calculated using the companion matrices of two compared images. Further, the rank of a symmetric matrix is used as similarity measure metric for defect detection. The numerical value of rank is zero for the defectless images and distinctly large for defective images. It is reliable and well tolerated to local variations and misalignment. The various experiments are carried out on the different PCB images. Moreover, the presented approach is tested in the presence of varying illumination and noise effect. Experimental results have shown the effectiveness of the proposed approach for detecting and locating the local defects in a complicated component-mounted PCB images.