• Title/Summary/Keyword: LCD Defect Inspection

Search Result 5, Processing Time 0.052 seconds

A Study on the Implementation of LCD Defect Inspection Algorithm (LCD 결함검사 알고리즘에 관한 연구)

  • 전유혁;김규태;김은수
    • Proceedings of the IEEK Conference
    • /
    • /
    • pp.637-640
    • /
    • 1999
  • In this Paper we show the LCD simulator for defect inspection using image processing algorithm and neural network. The defect inspection algorithm of the LCD consists of preprocessing, feature extraction and defect classification. Preprocess removes noise from LCD image, using morphology operator and neural network is used for the defect classification. Sample images with scratch, pinhole, and spot from real LCD color filter image are used. The proposed algorithms show that defect detected and classified in the ratio of 92.3% and 94.6 respectively.

  • PDF

Study on Machine Vision Algorithms for LCD Defects Detection (LCD 결함 검출을 위한 머신 비전 알고리즘 연구)

  • Jung, Min-Chul
    • Journal of the Semiconductor & Display Technology
    • /
    • v.9 no.3
    • /
    • pp.59-63
    • /
    • 2010
  • This paper proposes computer visual inspection algorithms for various LCD defects which are found in a manufacturing process. Modular vision processing steps are required in order to detect different types of LCD defects. Those key modules include RGB filtering for pixel defects, gray-scale morphological processing and Hough transform for line defects, and adaptive threshold for spot defects. The proposed algorithms can give users detailed information on the type of defects in the LCD panel, the size of defect, and its location. The machine vision inspection system is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithms are quite successful.

LCD Defect Detection using Neural-network based on BEP (BEP기반의 신경회로망을 이용한 LCD 패널 결함 검출)

  • Ko, Jung-Hwan
    • 전자공학회논문지 IE
    • /
    • v.48 no.2
    • /
    • pp.26-31
    • /
    • 2011
  • In this paper we show the LCD simulator for defect inspection using image processing algorithm and neural network. The defect inspection algorithm of the LCD consists of preprocessing, feature extraction and defect classification. Preprocess removes noise from LCD image, using morphology operator and neural network is used for the defect classification. Sample images with scratch, pinhole, and spot from real LCD color filter image are used. From some experiments results, the proposed algorithms show that defect detected and classified in the ratio of 92.3% and 94.5 respectively. Accordingly, in this paper, a possibility of practical implementation of the LCD defect inspection system is finally suggested.

Aberration Extraction Algorithm for LCD Defect Detection (대면적 LCD 결함검출을 위한 수차량 추출 알고리즘)

  • Ko, Jung-Hwan;Lee, Jung-Suk;Won, Young-Jin
    • 전자공학회논문지 IE
    • /
    • v.48 no.4
    • /
    • pp.1-6
    • /
    • 2011
  • In this paper we show the LCD simulator for defect inspection using image processing algorithm and neural network. The defect inspection algorithm of the LCD consists of preprocessing, feature extraction and defect classification. Preprocess removes noise from LCD image, using morphology operator and neural network is used for the defect classification. Sample images with scratch, pinhole, and spot from real LCD color filter image are used. From some experiments results, the proposed algorithms show that defect detected and classified in the ratio of 92.3% and 94.5 respectively. Accordingly, in this paper, a possibility of practical implementation of the LCD defect inspection system is finally suggested.

Defect Cell Extraction for TFT-LCD Auto-Repair System (TFT-LCD 자동 수선시스템에서 결함이 있는 셀을 자동으로 추출하는 방법)

  • Cho, Jae-Soo;Ha, Gwang-Sung;Lee, Jin-Wook;Kim, Dong-Hyun;Jeon, Edward
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.14 no.5
    • /
    • pp.432-437
    • /
    • 2008
  • This paper proposes a defect cell extraction algorithm for TFT-LCD auto-repair system. Auto defect search algorithm and automatic defect cell extraction method are very important for TFT-LCD auto repair system. In the previous literature[1], we proposed an automatic visual inspection algorithm of TFT-LCD. Based on the inspected information(defect size and defect axis, if defect exists) by the automatic search algorithm, defect cells should be extracted from the input image for the auto repair system. For automatic extraction of defect cells, we used a novel block matching algorithm and a simple filtering process in order to find a given reference point in the LCD cell. The proposed defect cell extraction algorithm can be used in all kinds of TFT-LCD devices by changing a stored template which includes a given reference point. Various experimental results show the effectiveness of the proposed method.