TFTLCD detection algorithm combining weighted template difference image and bilateral filtering
CSTR:
Author:
Affiliation:

1. Instrument Science and Optoelectric Engineering College, Hefei University of Technology, Hefei 230009, China; 2. Academy of Photoelectric Technology, Hefei University of Technology, Hefei 230009, China; 3. Key Laboratory of Special Display Technology of the Ministry of Education, Hefei 230009, China; 4. National Key Laboratory of Advanced Display Technology, Hefei 230009, China

Clc Number:

TP391.4

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    In order to detect common point and line defects on TFTLCD panels, a defect detection algorithm combining weighted template difference image method and bilateral filtering is proposed. The image is divided into several units with the same size, in which an ideal texture template with the size of l×k in the upper left corner is selected. These units are synthesized after subtracting the weighted template in order to remove most of the texture background. The suppression of residual texture background is achieved by bilateral filtering. The maximum entropy threshold segmentation method is used to realize the defect segmentation. Finally, the defect parameters in the image are extracted. It is proved that the algorithm can detect the defects on the TFTLCD panel image through testing the constructed theoretical defects image, and it is verified that the defects of pinhole, scratch and particles are successfully detected. The proposed algorithm combines the advantages of the wellbackgroundremoving performance of the difference image method and the effective denoising of bilateral filtering, which has good accuracy and applicability.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:
  • Revised:
  • Adopted:
  • Online: November 06,2017
  • Published:
Article QR Code