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In-TFT-Array-Process Micro Defect Inspection Using Nonlinear Principal Component Analysis
Department of Mechanical Engineering, Chung Yuan Christian University, Chungli, 320, Taiwan
Mechanical and Systems Research Laboratories, Industrial Technology Research Institute, Hsinchu 310, Taiwan
Institute of Optoelectronic Sciences, National Taiwan Ocean University, Keelung, 202, Taiwan
* Author to whom correspondence should be addressed.
Received: 3 September 2009; in revised form: 5 October 2009 / Accepted: 21 October 2009 / Published: 22 October 2009
Abstract: Defect inspection plays a critical role in thin film transistor liquid crystal display (TFT-LCD) manufacture, and has received much attention in the field of automatic optical inspection (AOI). Previously, most focus was put on the problems of macro-scale Mura-defect detection in cell process, but it has recently been found that the defects which substantially influence the yield rate of LCD panels are actually those in the TFT array process, which is the first process in TFT-LCD manufacturing. Defect inspection in TFT array process is therefore considered a difficult task. This paper presents a novel inspection scheme based on kernel principal component analysis (KPCA) algorithm, which is a nonlinear version of the well-known PCA algorithm. The inspection scheme can not only detect the defects from the images captured from the surface of LCD panels, but also recognize the types of the detected defects automatically. Results, based on real images provided by a LCD manufacturer in Taiwan, indicate that the KPCA-based defect inspection scheme is able to achieve a defect detection rate of over 99% and a high defect classification rate of over 96% when the imbalanced support vector machine (ISVM) with 2-norm soft margin is employed as the classifier. More importantly, the inspection time is less than 1 s per input image.
Keywords: thin film transistor liquid crystal display; TFT array process; automatic optical inspection; defect inspection; kernel principal component analysis; support vector machine
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Cite This Article
MDPI and ACS Style
Liu, Y.-H.; Wang, C.-K.; Ting, Y.; Lin, W.-Z.; Kang, Z.-H.; Chen, C.-S.; Hwang, J.-S. In-TFT-Array-Process Micro Defect Inspection Using Nonlinear Principal Component Analysis. Int. J. Mol. Sci. 2009, 10, 4498-4514.
Liu Y-H, Wang C-K, Ting Y, Lin W-Z, Kang Z-H, Chen C-S, Hwang J-S. In-TFT-Array-Process Micro Defect Inspection Using Nonlinear Principal Component Analysis. International Journal of Molecular Sciences. 2009; 10(10):4498-4514.
Liu, Yi-Hung; Wang, Chi-Kai; Ting, Yung; Lin, Wei-Zhi; Kang, Zhi-Hao; Chen, Ching-Shun; Hwang, Jih-Shang. 2009. "In-TFT-Array-Process Micro Defect Inspection Using Nonlinear Principal Component Analysis." Int. J. Mol. Sci. 10, no. 10: 4498-4514.