Segmentation of Defective Regions based on Logical Discernment and Multiple Windows for Inspection of TFT-LCD Panels

This paper proposes an image segmentation for a vision-based automated defect inspection system on surface image of TFT-LCD(Thin Film Transistor Liquid Crystal Display) panels. TFT-LCD images have non-uniform brightness, which is hard to finding defective regions. Although there are several methods or proposed algorithms, it is difficult to divide the defect with high reliability because of non-uniform properties in the image. Kamel and Zhao disclosed a method which based on logical stage algorithm for segmentation of graphics and character. This method is a one of the local segmentation method that has a advantage. It is that characters and graphics are well segmented in an image which has non-uniform property. As TFT-LCD panel image has a same property, so this paper proposes new algorithm to segment regions of defects based on Kamel and Zhao`s algorithm. Our algorithm has an advantage that there are a few ghost objects around the defects. We had experiments to prove performance in real TFT-LCD panel images, and comparing with the FFT(Fast Fourier Transform) method which is used a bandpass filter.