Research on Backlight Lens Light Pattern Control Based on Classification Learning Model
WANG Xianfan
PANG Bin
LI Yaosen
ZHANG Xiaoming
HE Yanjun
ZHANG Xuebing
LIANG Fei
Abstract：The light pattern parameter of the backlight lens can greatly influence the backlight effect of the liquid crystal display devices.Traditional measurement methods suffer from several issues such as strong subjectivity and low control accuracy.Here,a backlight lens light pattern measurement method based on a classification learning model is proposed.By extracting light intensity distribution features using CCD devices,a mapping model between light pattern parameters and overall backlight effect is constructed using a two-layer neural network.The experimental results demonstrate that the classification accuracy of the test set can achieve 96.97%for a certain reflective backlight lens using 163 samples.It is should be noted that the accuracy could be increased with sample amount.Finally,the proposed method is superior to the traditional parametric models and manual detection methods.
Keywords：backlight lensclassification learning modelliquid crystal display devicetwo-layer neural networklight pattern parameter measurement
Publication Date：2025-12-25
Online Publishing Date：2026-01-08(First online date of this platform, not the publication date of the document)
Pages：6( 13-18 )