LCD Edge Defects Detection Based On Digital Image Processing

In recent years,the rapid development of digital technology and people's pursuit of color and practicality of display devices have driven the development of display technology toward multi-function and digitization,and the display area has ushered in an iterative era of survival of the fittest.Liquid crystal display(LCD)stands out in the ever-changing technological innovation.Its advantages of low power consumption,low radiation,digitization,flatness,thinness,and multi-functionality are favored by many display devices.With the continuous development of liquid crystal display technology,LCD is widely used in mobile devices,outdoor advertising,operation panels,smart devices and other fields.LCD is an indispensable part of the display field of today's information technology era,and its detection process in the production process.Has a strict control over quality.This topic takes the edge detection algorithm of liquid crystal display(LCD)as the research object,and completes the design work of the LCD edge defect detection algorithm,aiming to solve the problems of high manual detection cost,low efficiency,and inability to guarantee the detection quality.Based on the experience of the edge detection,the edge detection method based on image processing was designed based on the experience of previous researchers.By analyzing the LCD image and understanding its digital characteristics,an image preprocessing scheme was designed.Image preprocessing has two functions.First,it separates the image with obvious defects on the edge;Second,it determines the area to be detected on the edge.The preprocessed image is detected and three kinds of flaw detection methods are designed.Correspond to three kinds of different digital features.According to the area to be detected determined by the pre-processing link,the image is first detected by two methods.If the detection results are inconsistent,a third type of detection is performed.The voting mechanism determines the value of the test data set.For the test data set,the detection rate reaches 100%.