There are direct visual and machine vision methods to detect MURA in LCD panels. The direct visual method shows inconsistent results depending on the status of testers and poor MURA detection performance. The machine vision detection method is not goo...
There are direct visual and machine vision methods to detect MURA in LCD panels. The direct visual method shows inconsistent results depending on the status of testers and poor MURA detection performance. The machine vision detection method is not good at detection of various forms of MURA. To solve these problems, this paper uses a representative model of machine learning, that is CNN(Convolutional Neural Network), to detect MURA. The CNN model used in this paper consists of five convolution layers and two fully connected layers. As a result of the experiment using the proposed method shows the 96% accuracy of MURA detection and takes 0.145 seconds for one panel test.