Bo GUO, Ju-hua GUAN, Zhi-kai HUANG. Automatic optical detection system for TFT-LCD spot-type defect based on improved Otsu algorithm[J]. Chinese journal of liquid crystals and displays, 2018, 33(3): 221-227.
DOI:
Bo GUO, Ju-hua GUAN, Zhi-kai HUANG. Automatic optical detection system for TFT-LCD spot-type defect based on improved Otsu algorithm[J]. Chinese journal of liquid crystals and displays, 2018, 33(3): 221-227. DOI: 10.3788/YJYXS20183303.0221.
Automatic optical detection system for TFT-LCD spot-type defect based on improved Otsu algorithm
In order to solve the problem that the traditional threshold segmentation algorithm is difficult to detect the spot-type defect from low contrast background
an improved Otsu algorithm is proposed.Based on this
a TFT-LCD spot-type defect automatic optical detection system is constructed.First
the effect of texture background is removed by Gabor filtering.Then
Using the different distribution characteristics of Weibull distribution function when the shape parameter of the Weibull function is segmented
the threshold extraction function of traditional Otsu is improved.Finally
offline test and online test are carried out.The experiment shows that the improved Otsu algorithm can produce better detection result than the traditional Otsu algorithm in the case of low contrast between defects and background.The algorithm is transplanted to the TFT-LCD spot-type defect automatic optical detection hardware platform to test.The correct detection rate can reach 94% and the detection time can be shortened to 150 ms.It reduces the workload and labor intensity of TFT-LCD manual spot-type defect detection.
LI X J, ZHAO Y L, LI P, et al.Prevention of TFT-LCD's "Spot issue"[J].Chinese Journal of Liquid Crystals and Displays, 2017, 32(7):507-511.(in Chinese)
TSENGY H. Independent component analysis approaches for process variation monitoring and Mura defect inspection in TFT-LCD manufacturing[D]. Taiwan: Yuan Ze University, 2013. (in Chinese)
CHEN S L, CHOU S T.TFT-LCD Mura defect detection using wavelet and cosine transforms[J].Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2008, 2(3):441-453.
TSAI D M, TSAI H Y.Low-contrast surface inspection of Mura defects in liquid crystal displays using optical flow-based motion analysis[J].Machine Vision and Applications, 2011, 22(4):629-649.
ZHANG T D, LU R S, DANG X M.Automatic neighbor r selection for one-dimensional DFT method in the surface defect inspection of TFT-LCD[J].China Mechanical Engineering, 2016, 27(21):2895-2901.(in Chinese)
ZHANG T D, LU R S.Automatic period selection for DFT method in the application of TFT-LCD panel detection[J].Journal of Electronic Measurement and Instrumentation, 2016, 30(3):361-373.(in Chinese)
LEE J Y, KIM T W, PAHK H J.Robust defect detection method for a non-periodic TFT-LCD pad area[J].International Journal of Precision Engineering and Manufacturing, 2017, 18(8):1093-1102.
BI X. Study on the methods of machine vision inspection for the Mura defect of TFT-LCD process[D]. Shanghai: Shanghai Jiao Tong University, 2009. (in Chinese)
CHEN Y Q, DUAN J, ZHU Y, et al.Research on the image complexity based on texture features[J].Chinese Optics, 2015, 8(3):407-414.(in Chinese)
MALARVEL M, SETHUMADHAVAN G, BHAGI P C R, et al.An improved version of Otsu's method for segmentation of weld defects on X-radiography images[J].Optik-International Journal for Light and Electron Optics, 2017, 142:109-118.
XU X Y, XU S Z, JIN L H, et al.Characteristic analysis of Otsu threshold and its applications[J].Pattern Recognition Letters, 2011, 32(7):956-961.