Autoencoder Display Unevenness Detection
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Solution Overview
Problem
The conventional manufacturing process of monitors is hindered by increased inspection time due to the reliance on human experience for detecting display unevenness, which can lead to inefficiencies in identifying defects such as luminance and chromaticity unevenness.
Innovation Solution
An information processing method utilizing an autoencoder to calculate errors and similarities between input and output image data, allowing for the determination of acceptable display unevenness based on a relational expression or table, thereby classifying image data by pixel value and pattern, thus reducing inspection time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection based on inspector experience is used to detect display unevenness, then detection capability is provided, but inspection time increases
Solution Approach 1:
The patent replaces manual visual inspection with an automated image processing system that captures display screen images and analyzes them using computer algorithms. The system calculates luminance values, determines display unevenness based on predetermined thresholds, and outputs inspection results automatically, eliminating the need for human inspectors to manually evaluate each display screen.
Solution Approach 2:
The inspection system performs self-evaluation by automatically capturing images, processing the image data, calculating luminance values, comparing them against thresholds, and determining whether display unevenness is present. The system serves itself by completing the entire inspection workflow without requiring human intervention in the actual inspection process.
2Productivity
If automated image processing is implemented to reduce inspection time, then inspection speed improves, but detection accuracy may deteriorate
Solution Approach 1:
The patent employs multiple parameter thresholds (first threshold, second threshold, third threshold) for luminance value comparisons to accurately classify different levels of display unevenness. By adjusting and optimizing these threshold parameters, the system maintains high detection accuracy while processing images rapidly through automated calculations and logical comparisons.
Solution Approach 2:
The inspection process is segmented into distinct operational stages: image capture, luminance value calculation, threshold comparison, and result determination. This segmentation allows each stage to be optimized independently, with the image processing portion handled rapidly by computer algorithms while the determination logic ensures accurate detection based on multiple threshold evaluations.
Data Source
AI summary
An object of the present invention is to provide an information processing method and a computer program that can suppress an increase in inspection time in the manufacturing process of the monitors.The present invention provides an information processing method comprising: an error calculation step of calculating an error between input image data input to an autoencoder and output image data output from the autoencoder; a similarity calculation step of calculating a similarity between compressed data and reference data based on the compressed data and the reference data, the compressed data being acquired by compressing the input image data in an encoder of the autoencoder; and a determination step of determining whether a display unevenness of the input image data is acceptable based on a relationship between the error and the similarity, the relationship corresponding to a relational expression or a table.