Research On Detection Method Of Image Defect For Mobile LCD Screen

With the rapid progress of technology and industry, LCD screen electronic products have become an integral part of our lives and production. Reality shows a higher and higher request on the quality of LCD screen of these products, while the current level of technology can not avoid sorts of defects. So, the first problem,which LCD manufactures need to face, is how to identify and solve the defects of the LCD screen rapidly and accurately. Current image defects of LCD products mainly rely on manual inspection that neither meet the accuracy detection of defects in LCD screen, nor guarantee the stability of test results.This thesis is precisely solves this problem as a starting point by using the mobile LCD screen as object of study and combining digital image processing, pattern recognition and computer technology, and in view of the common image defects, referring to the requirements of industrial production detection algorithm on efficiency and accuracy. This thesis have researched and designed an efficient detection algorithm. Simulation experiment results demonstrated my algorithm is efficiency and accurate on the image defects detection.First to standardize design of the mobile transmission system, and equip with acquisition equipments of appropriate models of high-speed image acquisition card, monitoring camera and computer equipment, complete the preparations of the hardware conditions. In the detection process, use surveillance camera to get the mobile image at first. And the images data are captured from the buffer of image acquisition card quickly by directshow technology. Then the weighted-averaged frame of bad frames could reduce the bad effect of the bad frames which are brought about by the harsh environment of image acquisition. In the image preprocessing stage, the noise will be removed by Gaussian pyramid sampling. Dynamic threshold value, getting from each RGB 3-channels by recursive iteration, will be helpful to detecting the screen rectangle by identifying and extracting shape feature of the image, and then using image two-dimensional geometric transformation to auto-correct the mobile position, extracting ROI. There is the end of image preprocessing. Finally, it detects the contours of defect using the Canny algorithm, and combine with Douglas-Peucker algorithm and Freeman chain code. It extracts the information of defect, and then testing the image defects of mobile screen:the number of bad pixels, geometric distortion, chromatic aberration. This algorithm is stable and efficient. It can be widely used in LCD products for image defect detection relying on the relevant national standards, and it is worth promoting.