Intensity Flow Estimation of Thin Film Transistor Liquid Crystal Display Panel Surface Image Using Multiweighted Morphology Pairs
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概要
- 論文の詳細を見る
In this paper, we present a new image enhancement method for a vision-based automated defect inspection system on the surface image of a thin film transistor liquid crystal display (TFT-LCD) panel. The TFT-LCD image has nonuniform brightness, which is a major difficulty in finding defective regions. The proposed method effectively estimates the nonuniform intensity variation except in defective regions using multiweighted morphological filters. After estimation, defects can be segmented easily using difference from the original image. Experimental results verified the performance of the proposed method.
- 2010-06-25
著者
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Kim Se-yun
School Of Electrical Engineering And Computer Science Kyungpook National University
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Song Young-chul
School Of Electrical Engineering And Computer Science Kyungpook National University
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Jung Chang-do
Department Of Mathematics Kyungpook National University
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Chang-Do Jung
Department of Mathematics, Kyungpook National University, Daegu 702-701, Korea
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Se-Yun Kim
School of Electrical Engineering and Computer Science, Kyungpook National University, Daegu 702-701, Korea
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Kil-Houm Park
School of Electrical Engineering and Computer Science, Kyungpook National University, Daegu 702-701, Korea
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Kil-Houm Park
School of Electrical Engineering and Computer Science, Kyungpook National University, 1370 Sankyuk-dong, Puk-gu, Daegu 702-701, Korea
関連論文
- A Development of the TFT-LCD Image Defect Inspection Method Based on Human Visual System
- Split Bregman Method-Based Background Extraction for Blob-Mura Defect Detection in Thin Film Transistor-Liquid Crystal Display Image
- Effective Defect Detection in Thin Film Transistor Liquid Crystal Display Images Using Adaptive Multi-Level Defect Detection and Probability Density Function
- Application of Piecewise Linear Regression Twice to Inspect The Defective Regions on Thin Film Transistor Liquid Crystal Display Panels
- Intensity Flow Estimation of Thin Film Transistor Liquid Crystal Display Panel Surface Image Using Multiweighted Morphology Pairs
- Double Self Quotient Image Based Image Flattening for Defect Detection in Thin Film Transistor Liquid Crystal Display Panel
- Kernel Adjusted Wiener Filter for Image Enhancement
- Anisotropic Diffusion Filter Based Blob-Mura Defect Detection in Thin Film Transistor Liquid Crystal Display Panel
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