Abstract
This research proposes a new automated visual inspection method to detect MURA-type defects (color non-uniformity regions) on Liquid Crystal Displays (LCD). Owing to their space saving, energy efficiency, and low radiation, LCDs have been widely applied in many high-tech industries. However, MURA-type defects such as screen flaw points and small color variations often exist in LCDs. This research first uses multivariate Hotelling T 2 statistic to integrate different coordinates of color models and constructs a T 2 energy diagram to represent the degree of color variations for selecting suspected defect regions. Then, an Ant Colony based approach that integrates computer vision techniques precisely identifies the flaw point defects in the T 2 energy diagram. The Back Propagation Neural Network model determines the regions of small color variation defects based on the T 2 energy values. Results of experiments on real LCD panel samples demonstrate the effects and practicality of the proposed system.
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References
Kido, T.: In Process Functional Inspection Technique for TFT-LCD Arrays. Journal of the SID 1, 429–435 (1993)
Chen, P.O., Chen, S.H., Su, F.C.: An Effective Method for Evaluating the Image-Sticking Effect of TFT-LCDs by Interpretative Modeling of Optical Measurement. Liquid Crystals 27, 965–975 (2000)
Pratt, W.K., Hawthorne, J.A.: Machine Vision Methods for Automatic Defect Detection in Liquid Crystal Displays. Advanced Imaging 13, 52–54 (1998)
Pratt, W.K., Sawkar, S.S., O’Reilly, K.: Automatic Blemish Detection in Liquid Crystal Flat Panel Displays. In: SPIE Symposium on Electronic Imaging: Science and Technology (1998)
Lee, J.Y., Yoo, S.I.: Automatic Detection of Region-Mura Defect in TFT-LCD. IEICE Transactions on Information and Systems E87-D(10), 2371–2378 (2004)
Taniguchi, K., Ueta, K., Tatsumi, S.: A Mura Detection Method. Pattern Recognition 39, 1044–1052 (2006)
Jiang, B.C., Wang, C.C., Liu, H.C.: Liquid Crystal Display Surface Uniformity Defect Inspection Using Analysis of Variance and Exponentially Weighted Moving Average Techniques. International Journal of Production Research 43(1), 67–80 (2005)
Lu, C.J., Tsai, D.M.: Defect Inspection of Patterned Thin Film Transistor-Liquid Crystal Display Panels Using a Fast Sub-image-based Singular Value Decomposition. International Journal of Production Research 42, 4331–4351 (2004)
Lu, C.J., Tsai, D.M.: Automatic Defect Inspection for LCDs Using Singular Value Decomposition. International Journal of Advanced Manufacturing Technology 25, 53–61 (2005)
Lowry, C.A., Montgomery, D.C.: A Review of Multivariate Control Charts. IIE Transactions 27, 800–810 (1995)
Mason, R.L., Chou, Y.M., Young, J.C.: Applying Hotelling’s T 2 Statistic to Batch Process. Journal of Quality Technology 33, 466–479 (2001)
Montgomery, D.C.: Introduction to Statistical Quality Control, 5th edn., pp. 491–504. John Wiley & Sons, Hoboken (2005)
Dorigo, M., Maniezzo, V., Colorni, A.: Ant System: Optimization by a Colony of Cooperating Agents. IEEE Transactions on Systems, Man, and Cybernetics-Part B 26, 29–41 (1996)
Dorigo, M., Bonabeau, E., Theraulaz, G.: Ant Algorithms and Stigmergy. Future Generation Computer System 16, 851–871 (2000)
Kang, B.S., Park, S.C.: Integrated Machine Learning Approaches for Complementing Statistical Process Control Procedures. Decision Support Systems 29, 59–72 (2000)
Smith, A.E.: X-bar and R Control Chart Interpretation Using Neural Computing. International Journal of Production Research 32, 309–320 (1994)
Hush, D.R., Horne, B.G.: Progress in Supervised Neural Networks. IEEE Signal Processing Magazine, 8–39 (January 1993)
Otsu, N.: A Threshold Selection Method from Gray Level Histograms. IEEE Transactions on Systems, Man and Cybernetics 9, 62–66 (1979)
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Lin, HD., Chiu, S.W. (2006). Computer-Aided Vision System for MURA-Type Defect Inspection in Liquid Crystal Displays. In: Chang, LW., Lie, WN. (eds) Advances in Image and Video Technology. PSIVT 2006. Lecture Notes in Computer Science, vol 4319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11949534_44
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DOI: https://doi.org/10.1007/11949534_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68297-4
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