Copyright © 2008 The Institute of Electronics, Information and Communication Engineers
Special Section on Image Media Quality - Papers |
A Development of the TFT-LCD Image Defect Inspection Method Based on Human Visual System
1 The authors are with the School of Electrical Engineering and Computer Science, Kyungpook National University, 1370, Sankyuk-dong, Buk-gu, Daegu 702-701, Korea. E-mail: khpark{at}ee.knu.ac.kr
The TFT-LCD image has non-uniform brightness that is the major difficulty of finding the visible defect called Mura in the field. To facilitate Mura detection, background signal shading should level off and Mura signal must be amplified. In this paper, Mura signal amplification and background signal flattening method is proposed based on human visual system (HVS). The proposed DC normalized contrast sensitivity function (CSF) is used for the Mura signal amplification and polynomial regression (PR) is used to level off the background signal. In the enhanced image, tri-modal thresholding segmentation technique is used for finding Dark and White Mura at the same time. To select reliable defect, falsely detected invisible region is eliminated based on Weber's Law. By the experimental results of artificially generated 1-d signal and TFT-LCD image, proposed algorithm has novel enhancement results and can be applied to real automated inspection system.
Key Words: TFT-LCD (thin film transistor-liquid crystal display), inspection, polynomial regression, human visual system, contrast sensitivity function
Manuscript received June 4, 2007. Manuscript revised November 28, 2007.
References
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