Extraction and evaluation of mura images in liquid crystal displays

Y. Mori, K. Tanahashi, R. Yoshitake, S. Tsuji

Research output: Contribution to journalConference articlepeer-review

11 Citations (Scopus)


The visual performance of liquid crystal displays (LCDs) has usually been evaluated by visual inspection during the manufacturing process. One of the visual problems hardest to recognize are regions of low-contrast and non-uniform brightness called muras. The accurate and consistent detection of the muras is extremely difficult because there are various shapes and sizes of muras and the inspection results tend to depend on the operators. We conducted a study on the quantitative evaluation of muras based on visual analysis, intending to clarify the detection method and create an automated mura inspection process. We developed an algorithm and a hardware system based on a commercially available CCD camera and a PC with an image processor board. This system can successfully identify and evaluate muras. The algorithm was developed from research on visual analysis and human perception. We converted the front-of-screen (FOS) images from the LCDs into distributions of luminance information, and the mura regions were distinguished from the background area using our novel algorithm. This approach also led to a weighting function for the categories of muras that appear in the panels. Our identification method can also distinguish between the muras caused by flaws in the LCD cells and the intentionally designed non-uniform luminance distribution of the backlight.

Original languageEnglish
Pages (from-to)299-306
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
Publication statusPublished - 2001 Dec 1
Externally publishedYes
EventAlgorithms and Systems for Optical Information Processing - San Diego, CA, United States
Duration: 2001 Jul 312001 Aug 2


  • Liquid crystal displays
  • Mura
  • Visual analysis
  • Visual performance

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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