LED Color Quality Detection Technology Based on Image Processing

Modern LED color quality detection systems (color calibration systems) often involve numerous color sensors and motors. Although this method has high detection accuracy, improper control of the motor can easily cause high-precision probes to collide with each other, causing unnecessary losses. In addition, if we want to further improve the utilization rate of calibration equipment, so that a machine can calibrate more light panels at the same time, relying solely on the increase in the number of motors and probes will lead to problems such as increased costs and reduced stability. If enough color information of LED can be collected through images and its quality can be successfully detected, it can get rid of the complex motor and color detection equipment, and even achieve the simultaneous detection of more lamp beads by one machine, thereby reducing detection costs. Therefore, this article combines image processing technology to first collect LED aperture color information, and then convert the color information into the HSL color space model for color quality analysis to determine whether the color quality is maintained within the allowable color difference range. This proves the possibility of using image processing technology to achieve LED color quality evaluation and provides theoretical support for further optimizing the color calibration system.