LED (Light Emitting Diode) is one of the fastest growing industries in the world today. The high brightness, low power consumption and long life of LED make LED display have obvious advantages in outdoor flat panel display. However, the difference in light and electrical characteristics between LEDs usually causes the brightness and chromaticity of the LED display to be inconsistent, which in turn destroys the white balance of the display, reduces the display quality, and causes problems such as flower screens and mosaics in severe cases. In solving this problem, the previous research mainly focused on the difference of the photoelectric characteristics of a single LED, the purpose is to find the appropriate compensation curve of RGB (red, green, blue) three primary color LEDs to correct its driving control parameters to improve the display effect. . This kind of detection and correction scheme can better solve serious problems such as flower screen and mosaic. However, even if there is a difference in characteristics between LEDs of the same primary color and the same batch, and LED full-color display screens contain many LED pixels, various problems will inevitably occur during production and manufacturing, which will lead to some The LED pixels are not lit, or the brightness and chromaticity are poor. Therefore, this type of detection scheme has a poor correction effect on a single LED pixel point, and the display effect is limited. As a compensation scheme, manual visual inspection can only detect individual LED pixels with obvious differences, and requires high debugging experience for the inspectors. At the same time, the high brightness of the LEDs also increases the working intensity of the inspectors, resulting in low detection efficiency. .

Therefore, this article starts from the outdoor full-color LED display, using digital image processing method to quickly detect each LED pixel on the display, in order to improve the detection speed and accuracy, thus improving the outdoor full-color LED display. Display effect.

1, detection principle

As shown in FIG. 1, the computer processes the display image of the LED display screen collected by the CCD (Charge Coupled Devices) sensor through the image acquisition/control module. The processing mainly includes the positioning of LED pixel points and the rapid detection of brightness and chromaticity.

1.1 LED pixel positioning

To determine the position of the LED pixel, first of all, the acquired LED display image is binarized. It is known from the histogram-based image threshold segmentation method that an image consists of one or more objects and backgrounds that can be separated with different gray levels. According to this principle, a plurality of peaks will appear in the histogram of the image, and each peak corresponds to an object or a background. To separate different objects, the peak value can be divided by the valley point as a threshold.

Due to the dot-matrix characteristics of the LED display screen, the acquired image is found in the actual detection (as shown in Fig. 2(a), the gray-scale histogram (Fig. 2(b)) has a bimodal distribution characteristic. For this type of situation, The maximum variance threshold method of (1) automatically selects the segmentation threshold, which is not only effective but also fast.

Figure 1 Schematic diagram of the detection system

Where T represents the segmentation threshold, w0 and w1 respectively represent the proportion of the pixel whose gradation value is less than T and greater than T in the image, and 0 and 1 respectively represent the gradation average of the image as a whole and the gradation value is less than T. The grayscale average of the portion of the image, and the grayscale value of the portion of the image whose grayscale value is greater than T.

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