A new algorithm on the automatic TFT-LCD mura defects inspection based on an effective background reconstruction

In this study, an automatic detection method for mura defects is developed based on an accurate reconstruction of the background and precise evaluation of the mura index level. To achieve this, an effective background reconstruction method is first developed to represent the brightness intensity of the display panel. As a result, any nonuniform brightness of the background can be removed effectively. Furthermore, the associated mura level is quantified based on the sensitivity of the human eye in order to alternatively grade the liquid-crystal display panels. The main focus of this study is on the reconstruction of the background from the display under test image. The proposed method takes full advantage of the following three existing methods: low-pass filtering, discrete cosine transform, and polynomial surface fitting. By applying the method to several case studies, we have shown that it is more effective compared with other existing methods in detecting various types of mura defects.