An improved image processing algorithm for automatic defect inspection in TFT-LCD TCON

The demand to improve image display in TFT-LCD, implementation of design for image processing is important. In order to meet the specific requirements of low-end Thin Film Transistor-Liquid-Crystal-Display (TFT-LCD) image display. This paper adopts a novel algorithm to conduct subsequent processing...

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Autores principales:	Yan Liyuan, Cengiz Korhan, Sharma Amit
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	timing control contrast eror diffusion matlab image processing rgb color model Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/d467cc7223444ae7acfc3179b179be07
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spelling	oai:doaj.org-article:d467cc7223444ae7acfc3179b179be072021-12-05T14:10:57ZAn improved image processing algorithm for automatic defect inspection in TFT-LCD TCON2192-80102192-802910.1515/nleng-2021-0023https://doaj.org/article/d467cc7223444ae7acfc3179b179be072021-10-01T00:00:00Zhttps://doi.org/10.1515/nleng-2021-0023https://doaj.org/toc/2192-8010https://doaj.org/toc/2192-8029The demand to improve image display in TFT-LCD, implementation of design for image processing is important. In order to meet the specific requirements of low-end Thin Film Transistor-Liquid-Crystal-Display (TFT-LCD) image display. This paper adopts a novel algorithm to conduct subsequent processing of the medical image after SCALER scaling, including contrast adjustment, gamma correction and dithering. Dithering algorithm is the focus of our research. After the study of some classical video image processing algorithms, and considering the real-time requirements, an intelligent algorithm is implemented for hardware implementation and improvement. For each part, MATLAB language is firstly used for advanced simulation to verify its feasibility, and then Right-To-Left (RTL) hardware language description is carried out. The characteristics extraction from images is performed implementing RGB standard and grayscale images. The pixel intensity is analyzed for each RGB component and the variance is calculated. When a panel displays a variation of 6% related with their reference values, the panel is rejected. The results obtained from classification shows a 95.24% accuracy rate in the detection of defects. The results of the two simulations show that the design achieves the expected goal, and the processing time is shorter.Yan LiyuanCengiz KorhanSharma AmitDe Gruyterarticletiming controlcontrasteror diffusionmatlabimage processingrgb color modelEngineering (General). Civil engineering (General)TA1-2040ENNonlinear Engineering, Vol 10, Iss 1, Pp 293-303 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	timing control contrast eror diffusion matlab image processing rgb color model Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	timing control contrast eror diffusion matlab image processing rgb color model Engineering (General). Civil engineering (General) TA1-2040 Yan Liyuan Cengiz Korhan Sharma Amit An improved image processing algorithm for automatic defect inspection in TFT-LCD TCON
description	The demand to improve image display in TFT-LCD, implementation of design for image processing is important. In order to meet the specific requirements of low-end Thin Film Transistor-Liquid-Crystal-Display (TFT-LCD) image display. This paper adopts a novel algorithm to conduct subsequent processing of the medical image after SCALER scaling, including contrast adjustment, gamma correction and dithering. Dithering algorithm is the focus of our research. After the study of some classical video image processing algorithms, and considering the real-time requirements, an intelligent algorithm is implemented for hardware implementation and improvement. For each part, MATLAB language is firstly used for advanced simulation to verify its feasibility, and then Right-To-Left (RTL) hardware language description is carried out. The characteristics extraction from images is performed implementing RGB standard and grayscale images. The pixel intensity is analyzed for each RGB component and the variance is calculated. When a panel displays a variation of 6% related with their reference values, the panel is rejected. The results obtained from classification shows a 95.24% accuracy rate in the detection of defects. The results of the two simulations show that the design achieves the expected goal, and the processing time is shorter.
format	article
author	Yan Liyuan Cengiz Korhan Sharma Amit
author_facet	Yan Liyuan Cengiz Korhan Sharma Amit
author_sort	Yan Liyuan
title	An improved image processing algorithm for automatic defect inspection in TFT-LCD TCON
title_short	An improved image processing algorithm for automatic defect inspection in TFT-LCD TCON
title_full	An improved image processing algorithm for automatic defect inspection in TFT-LCD TCON
title_fullStr	An improved image processing algorithm for automatic defect inspection in TFT-LCD TCON
title_full_unstemmed	An improved image processing algorithm for automatic defect inspection in TFT-LCD TCON
title_sort	improved image processing algorithm for automatic defect inspection in tft-lcd tcon
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/d467cc7223444ae7acfc3179b179be07
work_keys_str_mv	AT yanliyuan animprovedimageprocessingalgorithmforautomaticdefectinspectionintftlcdtcon AT cengizkorhan animprovedimageprocessingalgorithmforautomaticdefectinspectionintftlcdtcon AT sharmaamit animprovedimageprocessingalgorithmforautomaticdefectinspectionintftlcdtcon AT yanliyuan improvedimageprocessingalgorithmforautomaticdefectinspectionintftlcdtcon AT cengizkorhan improvedimageprocessingalgorithmforautomaticdefectinspectionintftlcdtcon AT sharmaamit improvedimageprocessingalgorithmforautomaticdefectinspectionintftlcdtcon
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An improved image processing algorithm for automatic defect inspection in TFT-LCD TCON

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