T/HBAI 001-2024 Active Group standards

T/HBAI 001-2024 Organic Light Emitting Diode Display Surface Mura Defect Quantification Methodology

Publish Date: 2024-10-17 Implement Date: 2024-10-25 For services related to genuine standard inquiry, procurement, translation, and other related services in China, please Contact Us

Price: $ 20.00

Out of stock

Basic Information

Standard Code: T/HBAI 001-2024

Standard Type: Group standards

Standard Status: Active

is_force_gb: no

CCS Name: -

ICS Name: Electronic display devices

Publish Date: 2024-10-17

Implement Date: 2024-10-25

Scope

Scope: This document specifies the grading standards and experimental conditions and methods for quantifying surface clouding (Mura) defects in organic light-emitting diode (OLED) displays. This document is primarily applicable to OLED displays. The main technical content of this document includes subjective experimental testing methods for quantifying Mura defects based on the spatial response of the human eye, and proposes calculation methods and quantification models for various factors of Mura defects, including multi-factor non-linear fitting models and neural network models based on MLP (Multi-Layer Perceptron). Main technical content: The main technical content of this document includes subjective experimental testing methods for quantifying Mura defects based on the spatial response of the human eye. This method adopts a double stimulus degree comparison experiment to reduce the influence of subjective factors on the experimental results. At the same time, it proposes calculation methods and quantification models for various factors of Mura defects, including multi-factor non-linear fitting models and neural network models based on MLP. By screening and processing the data obtained from the double stimulus degree comparison experiment, and conducting multi-factor non-linear fitting and neural network training and fitting based on MLP, multi-factor quantification formulas and neural network quantification models are obtained. The factors considered include the contrast of Mura defects, their size, and their type.