Defect Detection in Electronic Surfaces Using Template-Based Fourier Image Reconstruction

For defect detection in nonperiodical pattern images, such as printed circuit boards or integrated circuit dies found in the electronic industry, template matching could be the only applicable method to tackle the problem. The traditional template matching techniques work in the spatial domain and rely on the local pixel information. They are sensitive to geometric and lighting changes, and random product variations. The currently available Fourier-based methods mainly work for plain and periodical texture surfaces. In this paper, we propose a global Fourier image reconstruction method to detect and localize small defects in nonperiodical pattern images. It is based on the comparison of the whole Fourier spectra between the template and the inspection image. It retains only the frequency components associated with the local spatial anomaly. The inverse Fourier transform is then applied to reconstruct the test image, where the local anomaly will be restored and the common pattern will be removed as a uniform surface. The proposed method is invariant to translation and illumination, and can detect subtle defects as small as 1-pixel wide in a wide variety of nonperiodical patterns found in the electronic industry.