• Title/Summary/Keyword: TFT-LCD Defect Detection

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TFT-LCD Defect Blob Detection based on Sequential Defect Detection Method (순차적 결함 검출 방법에 기반한 TFT-LCD 결함 영역 검출)

  • Lee, Eunyoung;Park, Kil-Houm
    • Journal of Korea Society of Industrial Information Systems
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    • v.20 no.2
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    • pp.73-83
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    • 2015
  • This paper proposes a TFT-LCD defect blob detection algorithm using the sequential defect detection method. First, for every pixel, a defect possibility is determined by the intensity difference and the defect candidates are detected according to the sequential defect detection method. For detected candidate pixels, the defect probability that indicates a potential included in the defect according to the each step. By applying the morphological operation, blobs are comprised of the detected candidates and the defect blobs are detected using the defect possibility of blobs. The validity of the proposed method was demonstrated a simulated image and also then it was tested a real TFT-LCD image. By the experimental results, the proposed method is very effective in TFT-LCD detect detection.

Sequential Defect Region Segmentation according to Defect Possibility in TFT-LCD Image (TFT-LCD영상에서 결함 가능성에 따른 순차적 결함영역 분할)

  • Chang, Chung Hwan;Lee, SeungMin;Park, Kil-Houm
    • Journal of Korea Multimedia Society
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    • v.23 no.5
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    • pp.633-640
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    • 2020
  • Defect region segmentation of TFT-LCD images is performed by combining defect pixels detected by a defect detection method into defect region, or by using morphological operations to segment defect region. Therefore, the result of segmentation of the defect region is highly dependent on the defect detection result. In this paper, we propose a method which segments defect regions sequentially according to the possibility of being included in defect regions in TFT-LCD images. The proposed method repeats the process of detecting a seed using the median value and the median absolute deviation of the image, and segments the defect region using the seeded region growing method. We confirmed the superiority of the proposed method to segment defect regions using pseudo-images and real TFT-LCD images.

STD Defect Detection Algorithm by Using Cumulative Histogram in TFT-LCD Image (TFT-LCD 영상에서 누적히스토그램을 이용한 STD 결함검출 알고리즘)

  • Lee, SeungMin;Park, Kil-Houm
    • Journal of Korea Multimedia Society
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    • v.19 no.8
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    • pp.1288-1296
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    • 2016
  • The reliable detection of the limited defect in TFT-LCD images is difficult due to the small intensity difference with the background. However, the proposed detection method reliably detects the limited defect by enhancing the TFT-LCD image based on the cumulative histogram and then detecting the defect through the mean and standard deviation of the enhanced image. Notably, an image enhancement using a cumulative histogram increases the intensity contrast between the background and the limited defect, which then allows defects to be detected by using the mean and standard deviation of the enhanced image. Furthermore, through the comparison with the histogram equalization, we confirm that the proposed algorithm suppresses the emphasis of the noise. Experimental comparative results using real TFT-LCD images and pseudo images show that the proposed method detects the limited defect more reliably than conventional methods.

Defect detection for TFT-LCD panel using image processing (영상처리를 이용한 TFT-LCD의 불량 검출)

  • 이규봉;곽동민;최두현;송영철;박길흠
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.1783-1786
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    • 2003
  • In this paper, an automated line-defect detection method for TFT-LCD panel is presented. A DFB(Directional Filter Bank) and line-projection method are used to find line-defect which is one of the major defects occurred in TFT-LCD panel. The experimental results show that the proposed algorithm gave promising results for applying automated inspection technique for TFT-LCD panel.

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TFT-LCD Defect Detection Using Double-Self Quotient Image (이중 SQI를 이용한 TFT-LCD 결함 검출)

  • Park, Woon-Ik;Lee, Kyu-Bong;Kim, Se-Yoon;Park, Kil-Houm
    • Journal of KIISE:Computing Practices and Letters
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    • v.14 no.6
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    • pp.604-608
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    • 2008
  • The TFT-LCD image allows non-uniform illumination variation and that is one of main difficulties of finding defect region. The SQI (self quotient image) has the HPF (high pass filter) shape and is used to reduce low frequency-lightness component. In this paper, we proposed the TFT-LCD defect-enhancement algorithm using characteristics of the SQI, that is the SQI has low-frequency flattening effect and maintains local variation. The proposed method has superior flattening effect and defect-enhancement effect compared with previous the TFT-LCD image preprocessing.

A TFT-LCD Defect Detection Method based on Defect Possibility using the Size of Blob and Gray Difference (블랍 크기와 휘도 차이에 따른 결함 가능성을 이용한 TFT-LCD 결함 검출)

  • Gu, Eunhye;Park, Kil-Houm
    • Journal of Korea Society of Industrial Information Systems
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    • v.19 no.6
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    • pp.43-51
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    • 2014
  • TFT-LCD image includes a defect of various properties. TFT-LCD image have a recognizable defects in the human inspector. On the other hand, it is difficult to detect defects that difference between the background and defect is very low. In this paper, we proposed sequentially detect algorithm from pixels included in the defect region to limited defects. And blob analysis methods using the blob size and gray difference are applied to the defect candidate image. Finally, we detect an accurate defect blob to distinguish the noise. The experimental results show that the proposed method finds the various defects reliably.

A study on the detection probabilities of pixel defects with respect to their locations on the TFT-LCD (TFT-LCD의 품질검사기준 설정을 위한 픽셀결점 탐지도 평가)

  • 김상호;양승준
    • Proceedings of the Safety Management and Science Conference
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    • 2004.05a
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    • pp.283-289
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    • 2004
  • The number of pixel defects including bright and black dots on a panel is one of the critical factors determining the quality of TFT-LCD. Since pixel defects on the TFT-LCD panels are sometimes unavoidable, manufacturers have to inspect the panels so that any panel with an unacceptable number of defects will not be delivered to the buyers. However, the buyers demand for the manufacturers to meet different pixel defects tolerances (acceptable number of pixel defects on a TFT-LCD panel) around central(tight) and peripheral(loose) inspection zones. The disagreement in quality standard among different buyers also cause confusions in screening non-confirmative products and unstable yield of production. Few research has focused on the effects of defect locations on a TFT-LCD panel on their detection probabilities and the rational division of defect inspection zones. In this research, experiments were conducted to find the detection probabilities of black dot defects with respect to their varying locations on a TFT-LCD. It is proposed a rational division of inspection zone on a TFT-LCD panel on the basis of detection probabilities of the defects. With these division of inspection zones and the mean defect detection probability within each zone, it is expected to establish a more reasonable pixel defects tolerances.

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TFT-LCD Defect Detection based on Histogram Distribution Modeling (히스토그램 분포 모델링 기반 TFT-LCD 결함 검출)

  • Gu, Eunhye;Park, Kil-Houm;Lee, Jong-Hak;Ryu, Gang-Soo;Kim, Jungjoon
    • Journal of Korea Multimedia Society
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    • v.18 no.12
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    • pp.1519-1527
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    • 2015
  • TFT-LCD automatic defect inspection system for detecting defects in place of the visual tester does pre-processing, candidate defect pixel detection, and recognition and classification through a blob analysis. An over-detection result of defects acts as an undue burden of blob analysis for recognition and classification. In this paper, we propose defect detection method based on the histogram distribution modeling of TFT-LCD image to minimize over-detection of candidate defective pixels. Primary defect candidate pixels are detected estimating the skewness of the luminance distribution histogram of the background pixels. Based on the detected defect pixels, the defective pixels other than noise pixels are detected using the distribution histogram model of the local area. Experimental results confirm that the proposed method shows an excellent defect detection result on the image containing the various types of defects and the reduction of the degree of over-detection as well.

Detection of TFT-LCD Defects Using Independent Component Analysis (독립성분분석을 이용한 TFT-LCD불량의 검출)

  • Park, No-Kap;Lee, Won-Hee;Yoo, Suk-In
    • Journal of KIISE:Software and Applications
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    • v.34 no.5
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    • pp.447-454
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    • 2007
  • TFT-LCD(Thin Film transistor liquid crystal display) has become actively used front panel display technology with increasing market. Intrinsically there is region of non uniformity with low contrast that to human eye is perceived as defect. As the gray level difference between the defect and the background is hardly distinguishable, conventional thresholding and edge detection techniques cannot be applied to detect the defect. Between the patterned and un-patterned LCD defects, this paper deals with un-patterned LCD defects by using independent component analysis, adaptive thresholding and skewness. Our method showed strong results even on noised LCD images and worked successfully on the manufacturing line.

Sequential Defect Detection According to Defect Possibility in TFT-LCD Panel Image (TFT-LCD 패널 영상에서 결함 가능성에 따른 순차적 결함 검출)

  • Lee, SeungMin;Kim, Tae-Hun;Park, Kil-Houm
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.4
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    • pp.123-130
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    • 2014
  • In TFT-LCD panel images, defects are typically detected by using a large difference in the brightness compared to the background. In this paper, we propose a sequential defect detection algorithm according to defect possibility caused by difference of brightness. By using this method, pixels with high defect probabilities are preferentially detected and defects with a large brightness difference are accurately detected. Also, limited defects with a small brightness difference is detected more reliably, eventually minimizing the degree of over-detection. We have experimentally confirmed that our proposed method showed an excellent detection result for detecting limited defects as well as defects with a large brightness difference.