How to Use Imaging Colorimeters for Automated Visual Inspection of Displays in Production

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BY RADIANT VISION SYSTEMS, LLC

Introduction

From LCD to OLED to QLED, displays of all kinds are subject to a range of defects introduced either at their component-level or as a result of errors during production. For LCDs and other backlit displays, defects may occur at any position within the many layers that make up the display as a result of anomalies introduced between the layers or manufacturing stress during layer application. For emissive displays like LEDs, OLEDs, and mini- or microLEDs, defects are often inherent at the pixel and subpixel level, where different output luminance at the emitting element may cause variation in brightness and color. Because no production process can guarantee consistency for every single display produced, quality testing for every display on the line is critical.

There are three main approaches to visual inspection of illuminated displays in production—whether in line, or at the end of the line for final qualification:

1.Human inspection – Easily handles moderately complex testing requirements. Relatively slow and variable when compared to electronic testing methods.
2.Machine vision-based inspection – Very fast for simple tests. Does not reflect human visual experience for many tests.
3.Imaging colorimeter-based inspection – Somewhere between the preceding two methods in speed. Replicates human eye sensitivity to light with a very high degree of reliability and repeatability.

The use of imaging colorimeter systems and associated analytical software to assess display brightness, color uniformity, and contrast—and to identify defects in displays—is well established. A fundamental difference between imaging colorimetry and machine vision is imaging colorimetry’s accuracy in matching human visual perception for light and color uniformity (and non-uniformity).
In this article, we will describe how imaging colorimetry can be used in a fully-automated testing system to identify and quantify defects in high-speed, high-volume production environments. We will also cover the test setup and the range of tests that can be performed—spanning simple point defect detection through complex mura detection and evaluation.
Measurement Challenges

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