Development of OLED panel defect detection system through improved otsu algorithm

  • Authors:

  • Jian Gao;Zhiliang Wang;Yanyun Liu;Chuanxia Jian;Xin Chen

  • Affiliations:

  • Key Laboratory of Mechanical Equipment Manufacturing & Control Technology, Ministry of Education, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, China;Key Laboratory of Mechanical Equipment Manufacturing & Control Technology, Ministry of Education, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, China;Key Laboratory of Mechanical Equipment Manufacturing & Control Technology, Ministry of Education, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, China;Key Laboratory of Mechanical Equipment Manufacturing & Control Technology, Ministry of Education, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, China;Key Laboratory of Mechanical Equipment Manufacturing & Control Technology, Ministry of Education, School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, China

  • Venue:
  • ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part II
  • Year:
  • 2012

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Abstract

OLED (Organic light-emitting) displays have been called the next generation of display devices for their unique properties: colorful images, large viewing angle, light weight and power efficiency. Complex manufacture processing makes the screen have some defects. Detecting the defects will help to improve the quality. In this paper we concentrate on detecting these defects and proposed a corner-points based method, where the corner-points are extracted from the skeleton image and used as the control points for the subtract operation. We proposed an improved Otsu method to determine the image segmentation threshold by recursive process. Based on the algorithm proposed, a system for OLED screen defect detection was developed. The test result shows that the developed system can detect most of the defects on the panel.