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Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. Automatic Detection of Region-Mura Defect in TFT-LCD Yong-Hyeon.

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Presentation on theme: "Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. Automatic Detection of Region-Mura Defect in TFT-LCD Yong-Hyeon."— Presentation transcript:

1 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Automatic Detection of Region-Mura Defect in TFT-LCD Yong-Hyeon Hwang Kowon.dongseo.ac.kr/~d0066042

2 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Contents Introduction Local Segmentation Background Surface Estimation Problem Works as follows

3 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Introduction Otsu's methodGradient magnitude image Input Image

4 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Local Segmentation

5 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Background Surface Estimation The data set is approximated by a bivariate polynomial model of order d f ( d ) ( x ; y ) = X m + n · d a mn x m y n f ( d ) ( x ; y ) f ( d ) ( x ; y ) = X i + j · d a ij x i y j 식 변환

6 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Background Surface Estimation is the difference between the original and the estimated intensity of the data pixel given by the model parameters are estimated by minimizing the sum of the squared residuals r xy r xy m i n X x ; y r 2 xy r xy = z xy ¡ f ( d ) ( x ; y )

7 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Problem because even a single aberrant data point d = 4 outlier d = 1

8 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Works as follows Input Image

9 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Works as follows Remove p from the data set Determine the polynomial of order fitting denoted by using the LS. l f ( l ) ¡ p ª ¡ p = ª ¡ f p g ª ¡ p

10 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Works as follows Compute the diagnostic measure J ( p ) J ( p ) = 1 WH ¡ 1 X ª ¡ 1 j z xy ¡ f ( l ) ¡ p ( x ; y )j Diagnistic measure J

11 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Works as follows Construct a binary image

12 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Works as follows Apply median filtering to the binary image

13 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Works as follows Estimated background Suface f ( h ) B Remove probable outliers(white pixel)

14 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Works as follows Determine the polynomial of order h fitting Absolute residuals with respect to f ( h ) B

15 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Works as follows Thresholding result

16 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Works as follows Post-Processing result

17 Graphics Programming 2007 Hwang Yong-Hyeon Dongseo Univ. E-mail:pial051@dit.dongseo.ac.kr Result Biquadratic(d=2) biquartic (d = 4) Biquadratic(d=2)biquartic (d = 4)


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