An effective defect inspection system for polarized film images using image segmentation and template matching techniques

In this paper, we present an effective defect inspection system that identifies film defects and determines their types in order to produce polarized films for TFT-LCD (thin film transistor – liquid crystal display). The proposed system is designed and implemented to find defects from polarized film images using image segmentation techniques and to determine defect types through the image analysis of detected defects using template matching techniques. We extract features of the defects such as shape and texture, and compare them to the features of referential defect images stored in a template database. Experimental results using the proposed system show that it identifies defects of test images effectively (Recall = 1.00, Precision = 0.95) and efficiently (Average response time = 0.64 s), and also achieves a high correctness in determining the types (Recall = 0.95, Precision = 0.96) for five classes of defects. In addition the experiment shows that our system is fairly robust with respect to the rotational transformation, achieving the desirable property of the rotation invariance.