Luminance uniformity evaluation for backlight based on &epsilon;-support vector regression

SONG Yue; LIN Zhi-xian; YAO Jian-min; GUO Tai-liang

doi:10.3788/YJYXS20153005.0857

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Luminance uniformity evaluation for backlight based on ε-support vector regression

Imaging Technology & Image Processing | 更新时间：2020-08-12

- Luminance uniformity evaluation for backlight based on ε-support vector regression
- Chinese Journal of Liquid Crystals and Displays Vol. 30, Issue 5, Pages: 857-863(2015)
- 作者机构：
  
  福州大学物理与信息工程学院,福建福州,350002
- 作者简介：
- 基金信息：
- DOI：10.3788/YJYXS20153005.0857
  CLC： TP752
- Received：28 September 2014，
  
  Revised：04 November 2014，
  
  Published Online：10 November 2014，
  
  Published：05 October 2015
- 稿件说明：
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宋悦, 林志贤, 姚剑敏, 郭太良. 基于<em>ε</em>-支持向量回归机的背光源亮度均匀性评价方法[J]. 液晶与显示, 2015,30(5): 857-863

SONG Yue, LIN Zhi-xian, YAO Jian-min, GUO Tai-liang. Luminance uniformity evaluation for backlight based on ε-support vector regression[J]. , 2015,30(5): 857-863
宋悦, 林志贤, 姚剑敏, 郭太良. 基于<em>ε</em>-支持向量回归机的背光源亮度均匀性评价方法[J]. 液晶与显示, 2015,30(5): 857-863 DOI： 10.3788/YJYXS20153005.0857.

SONG Yue, LIN Zhi-xian, YAO Jian-min, GUO Tai-liang. Luminance uniformity evaluation for backlight based on ε-support vector regression[J]. , 2015,30(5): 857-863 DOI： 10.3788/YJYXS20153005.0857.

摘要

针对现有传统亮度计采集背光源亮度的检测方法用时长

不适于生产线的问题

提出一种基于

-支持向量回归机的背光源亮度均匀性评价方法。设计了背光源亮度均匀性检测平台

采用CCD图像传感器一次性同时获得几个背光源亮度图像

并进行校正。通过在非线性条件下的

-支持向量回归机(

-SVR)对校正后得到的背光源检测点亮度值构建关于背光源亮度值的预测模型

并对若干个背光源进行预测

与检测标准相比较判断其亮度是否合格。结果表明

在构建的支持向量回归模型中多种参数的融合检测

其精度是相似的。其中

最佳预测结果RMSE为43.28

BR为1.21%。说明预测结果与传统亮度计的测量值之间误差较小

但操作方便、且所用时间更短

对于背光源亮度均匀性的客观评价与亮度计评价结果基本符合。

Abstract

The traditional luminance meter takes too much time to detect the backlight luminance so that it is hard to take bulk-production in the engineering practice. To solve these problems

the paper puts forward an evaluation method of backlight luminance uniformity based on

-support vector regression. A backlight luminance uniformity testing platform is designed. First of all

a CCD image sensor is used in a single shot to get a digital image of several backlights

and the image is corrected. Secondly uses

-support vector regression (

-SVR) in the condition of nonlinear to test the luminance values of check points in backlights

and forecast the real luminance values of backlights. At last

it is compared with the testing standard to judge whether the backlights are qualified. The results show that the fusion of parameters can be tested in the constructed support vector regression. And their accuracy shows good similarity. RMSE of the best prediction is 43.28

BR is 1.21%. The error between the predicted results and these results of the measurements of the traditional luminance meter is much less

and it is easy to operate. The evaluation results of luminance meter are accorded with the method of the objective evaluation of the backlight luminance uniformity.

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references

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Luminance uniformity evaluation for backlight based on ε-support vector regression

DOI：10.3788/YJYXS20153005.0857

摘要

Abstract

关键词

Keywords

references