Automatic mura detection system for liquid crystal display panels

Li Te Fang*, Hsin Chia Chen, I. Chieh Yin, Sheng-Jyh Wang, Chao Hua Wen, Cheng Hang Kuo

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

In this paper, we propose an automatic inspection system, which can automatically detect four types of muras on an LCD panel: cluster mura, v-band mura, rubbing mura, and light leakage mura. To detect cluster muras, the Laplacian of Gaussian (LOG) filter is used. A multi-resolution approach is proposed to detect cluster muras of different scales. To speed up the processing speed, this multi-resolution approach is actually implemented in the frequency domain. To detect v-band muras, we check the variation tendency of the projected 1-D intensity profile. Then, v-band muras are detected by identifying these portions of the 1-D profile where a large deviation occurs. To detect rubbing muras, we designed a frequency mask to detect distinct components in the frequency domain. To detect light leak muras, we apply image mirroring over the boundary parts and adopt the same LOG filter that has been used in detecting cluster muras. All four types of mura detection are integrated together in an efficient way and simulation results demonstrate that this system is indeed very helpful in detecting mura defects.

Original languageEnglish
Title of host publicationMachine Vision Applications in Industrial Inspection XIV - Proceedings of SPIE-IS and T Electronic Imaging
DOIs
StatePublished - 17 Apr 2006
EventMachine Vision Applications in Industrial Inspection XIV - San Jose, CA, United States
Duration: 16 Jan 200617 Jan 2006

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6070
ISSN (Print)0277-786X

Conference

ConferenceMachine Vision Applications in Industrial Inspection XIV
CountryUnited States
CitySan Jose, CA
Period16/01/0617/01/06

Keywords

  • Automatic inspection
  • Laplacian of Gaussian
  • Mura defect
  • Mura detection
  • SEMU

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