Abstract
The visual performance of liquid crystal displays (LCDs) has been usually inspected and evaluated by sensory analysis at the manufacturing process. One of the most indistinct visual problems is low-contrast non-uniform brightness region 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 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.
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