Detection method and device for image residue of liquid crystal panel

Abstract

The invention provides a detection method and device for image residue of a liquid crystal panel. The method comprises after the liquid crystal panel displays a standard checkerboard picture for a time value, changing the picture into a designated gray scale and obtaining an image residue image; performing Fourier transform on a digital image of the standard checkerboard picture and the image residue image to obtain a first energy frequency spectrum and a second energy frequency spectrum; converting the first energy frequency spectrum and the second energy frequency spectrum into polar coordinates to become functions related to a polar angle and frequencies, and performing 0-2pi summation under each frequency with respect to the polar angle, thus obtaining a checkerboard energy frequency spectrum and a residue image energy frequency spectrum; solving a characteristic frequency corresponding to a maximal energy value in all energy values of the checkerboard frequency spectrum; solving frequencies of the residue image energy frequency spectrum as a first energy value and a second energy value corresponding to the characteristic frequency and a zero frequency; dividing the second energy value with the first energy value to obtain a residue image evaluation value.

Description

technical field [0001] The invention relates to the field of liquid crystal panel manufacturing, in particular to a liquid crystal panel image residual detection method and device based on digital image processing. Background technique [0002] In the design and production process of the LCD panel, the LCD panel will be tested for Image Sticking, that is, by making the LCD panel stay on one screen (such as a checkerboard screen) for a long time, after changing the display content, observe whether the residue remains. A screen shown earlier. The generation of image sticking is related to the material, process and circuit design of the panel. Generally, the detection of image retention is based on the "Just-noticeable Differences" (JND) model based on the judgment of the human eye. This method has high labor costs and high subjective factors, making it difficult to objectively and quantitatively describe the degree of image retention. SUMMARY OF THE INVENTION [0003] In v...

AI Technical Summary

Problems solved by technology

The general basis for detecting image retention is based on the "just-noticeable differences" model (Just-noticeable differences, JND) judged by the human eye. This method has high labor costs and high subjective factors, making it difficult to describe the degree of image retention objectively and quantitatively.

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