Abstract

An analytical approach using human perception has been introduced to evaluate the front-of-screen (FOS) quality of liquid crystal displays (LCDs), in particular regarding the regions of the liminance non-uniformity called "mura". The word "mura" is a Japanese term similar to "blemish" and has been adopted in English to provide a precise name for certain imperfections of the display pixel matrix surfaces that are visible when the display is in active use. The accurate and consistent detection of the mura is extremely difficult because there are various shapes and sizes of mura and the inspection results tend to depend on the inspectors during the LDC manufacturing process. We conducted a study on the quantitative evaluation of mura based on visual analysis, intending to clarify the detection method and create an automated mura inspection process. We developed an algorithm to extract and evaluate mura by using 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 mura. 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. In order to further match the evaluation results of mura to human perceptions, we conducted a perception test with some expert inspectors by using pseudo mura and this approach led to categorizing "just noticeable differences" according to the varieties of mura. This paper describes the research in human perception and the approach adapting the intrinsic rules of sensory analysis to the quantitative evaluation of mura.

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