Defect detection using feature point matching for non-repetitive patterned images

Defect detection is an important technology for the quality control in the production process of wafer, TFT-LCD and PCB. Inspection is performed using the finished product’s image. The images are classified into two different groups—images with a repetitive pattern on a regular cycle and images without a repetitive pattern. A standard object for comparison is required, because manual defect detection is not possible for areas without repetitive patterns. In such areas, defect detection occurs through contrasting a reference pattern to the pattern being inspected. Methods of inspection using reference image have been researched but have limitations due to their requirement of precise alignment of the images. This paper proposes a method of defect detection to overcome such limitation using feature point matching. Feature points are extracted using a corner detector and detects defect by finding a correspondence between two feature point sets. Performance of the proposed method is evaluated by using Wafer SEM images and compared with conventional methods. Experiment results demonstrate the proposed method achieves higher detection accuracy than conventional methods and is less sensitive to alignment error and noise.