2006Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIERequires access

A novel display metrology method for LED backlight system

Jee‐Gong Chang, Lun‐De Liao, Chi‐Chuan Hwang

Open publisher page 1 citations

Abstract

This study develops a statistical prediction model for backlight systems based on a semi-analytical and experimental approach. The prediction model features an iteration algorithm which uses experimental measurements of the luminance, luminance cone angle and luminous efficiency to generate highly accurate luminance predictions. The prediction model allows the effects of manufacturing errors or uncertainties which cause a deviation of the luminance cone angle or an uneven luminance uniformity to be accessed. The results show that achieving an even luminance cone angle, i.e. a smaller mean and standard deviation of the luminance cone angle, is essential if the backlight luminance level required to achieve a high-brightness backlight is to be enhanced. It is shown that improving the luminance uniformity of the backlight is beneficial in increasing the luminance level. However, the influence of the backlight luminance uniformity is not as great as that of the luminance cone angle. Finally, a comparison between the analytical and experimental results shows that a good agreement exists between the results of the proposed statistical model and the experimental data.

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What this paper is about

This study develops a statistical prediction model for backlight systems based on a semi-analytical and experimental approach. The prediction model features an iteration algorithm which uses experimental measurements of the luminance, luminance cone angle and luminous efficiency to generate highly accurate luminance predictions. The prediction model allows the effects of manufacturing errors or uncertainties which cause a deviation of the luminance cone angle or an uneven luminance uniformity to be accessed. The results show that achieving an even luminance cone angle, i.e. a smaller mean and standard deviation of the luminance cone angle, is essential if the backlight luminance level required to achieve a high-brightness backlight is to be enhanced. It is shown that improving the luminance uniformity of the backlight is beneficial in increasing the luminance level. However, the influence of the backlight luminance uniformity is not as great as that of the luminance cone angle. Finally, a comparison between the analytical and experimental results shows that a good agreement exists between the results of the proposed statistical model and the experimental data.

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Available abstract

This study develops a statistical prediction model for backlight systems based on a semi-analytical and experimental approach. The prediction model features an iteration algorithm which uses experimental measurements of the luminance, luminance cone angle and luminous efficiency to generate highly accurate luminance predictions. The prediction model allows the effects of manufacturing errors or uncertainties which cause a deviation of the luminance cone angle or an uneven luminance uniformity to be accessed. The results show that achieving an even luminance cone angle, i.e. a smaller mean and standard deviation of the luminance cone angle, is essential if the backlight luminance level required to achieve a high-brightness backlight is to be enhanced. It is shown that improving the luminance uniformity of the backlight is beneficial in increasing the luminance level. However, the influence of the backlight luminance uniformity is not as great as that of the luminance cone angle. Finally, a comparison between the analytical and experimental results shows that a good agreement exists between the results of the proposed statistical model and the experimental data.

Key concepts: Backlight, Luminance, Brightness, Optics, Computer science, Standard deviation, Contrast ratio, Ligand cone angle

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