A Development of the TFT-LCD Image Defect Inspection Method Based on Human Visual System

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概要

• 論文の詳細を見る

• 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, trimodal 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 Webers 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.

• （社）電子情報通信学会の論文
• 2008-06-01

著者

• PARK Kil-Houm

  School of Electrical Engineering and Computer Science, Kyungpook National University

• Oh Jong-hwan

  School Of Electrical Engineering And Computer Science Kyungpook National University

• Park Kil-houm

  School Of Electrical Engineering And Computer Science Kyungpook National University

• YUN Byoung-Ju

  School of Electrical Engineering and Computer Science, Kyungpook National University

• KIM Se-Yun

  School of Electrical Engineering and Computer Science, Kyungpook National University

• Kim Se-yun

  School Of Electrical Engineering And Computer Science Kyungpook National University

• Yun Byoung-ju

  School Of Electrical Engineering And Computer Science Kyungpook National University

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• Robust Defect Size Measurement Using 3D Modeling for LCD Defect Detection in Automatic Vision Inspection System
• A Development of the TFT-LCD Image Defect Inspection Method Based on Human Visual System
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