Mura Detection on OLED Displays via Spatial Frequency Filtering

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Solution Overview

Problem

Mura defects on OLED displays are difficult to detect due to their varied shapes and sizes, and existing methods rely on subjective human visual inspection, leading to inefficient and inconsistent classification and labeling.

Innovation Solution

An image processing device and method that segments display images into region of interest patches, filters out specific spatial frequency components, and identifies mura defects using predetermined patterns, mimicking human visual perception to enhance detection accuracy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If human visual inspection is used for mura detection, then subjective assessment can be performed, but consistency and efficiency are poor

Engineering Contradiction:

Improvemura detection accuracyVSAvoiddetection efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent replaces the mechanical human visual inspection system with an automated image processing system that uses spatial frequency filtering and pattern matching algorithms to detect and classify mura defects, thereby improving both consistency and efficiency

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent transforms the detection approach by changing from direct visual assessment to analyzing spatial frequency components of the display image, enabling automated detection while maintaining accuracy through mathematical transformation and pattern recognition

Inventive Principle:

Principle #35Parameter changes

2Reliability

If human visual inspection is used for mura detection, then detection can be performed, but classification and labeling are inconsistent

Engineering Contradiction:

Improvedetection consistencyVSAvoidclassification complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent replaces subjective human classification with an automated pattern matching system that compares filtered image regions against predetermined mura patterns, ensuring consistent and reliable classification and labeling of different mura defect types

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent transforms complex visual classification into a systematic process by converting image data into spatial frequency domain and matching against standardized patterns, thereby improving reliability while managing complexity through algorithmic approaches

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If full spatial frequency components are analyzed, then complete image information is available, but detection accuracy is reduced due to background interference

Engineering Contradiction:

Improvemura detection precisionVSAvoidimage information loss

Core Design Contradiction:

Measurement precisionVSLoss of information

Solution Approach 1:

The patent extracts only the relevant spatial frequency components that correspond to human visual perception and mura defect characteristics, filtering out background interference frequencies while preserving essential defect information for accurate detection

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent applies different processing to different spatial frequency components, enhancing frequencies associated with mura defects while suppressing background frequencies, thereby improving detection precision without losing critical defect information

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11676265B2Method and image processing device for mura detection on display

Publication Date: 2023.06.13 NOVATEK MICROELECTRONICS CORP

AI summary

A method and an image processing device for mura detection on a display are proposed. The method includes the following steps. An original image of the display is received and segmented into region of interest (ROI) patches. A predetermined range of spatial frequency components are filtered out from the ROI patches to generate filtered ROI patches. A mura defect is identified from the display according to the filtered ROI patches and predetermined mura patterns.