Research Of The QR Code Based On Image Preprocessing

With the development of information technology, automatic identification technology in the application of information technology industry is more and more widely, its role is particularly important. One-dimensional bar code has been widely used in our daily life, also greatly enhanced the productivity, but the one dimensional code has a lot of shortcomings, such as little information reserved, relying on a small database, increasingly emerging. QR code has a large amount of advantages,such as informative, information security,large information density and the decoding error correction ability, high safety, can store text and image and all kinds of website information. In many automatic identification technology, bar code technology plays an important role. In the modern business activities, with the popularity of smartphones and all kinds of mobile intelligent device, which can realize the application is very extensive. But in practice, influenced by acquisition equipment, collection of images tend to have all kinds of noise, affect the late effect of decoding.Image preprocessing technique is formally in the image processing to do a series of pretreatment before the operation, including grayscale, binarization and enhance recovery, etc. Due to the image collection, image transmission and storage process inevitably by different kinds of noise pollution and destroy of all kinds of dirty,lead to the resulting image and the target image has great deviation, so I need a series of preprocessing operations to eliminate the impact on image.In this paper, through theoretical analysis and simulation experiment, by reading a lot of the relevant image preprocessing papers, in reference on the basis of predecessors’ research results, studies the QR code image preprocessing method based on image processing.Realize the denoising of QR codes, and the shadow and correction space deformation QR codes, the paper main content and innovation points are as follows:In order to decode the reliability and stability of the late, with smart phones and mobile devices collect images have shadows and space of tilt of the QR code, for example, on the image gray, the median filter for processing. Effectively reduce the influence of noise on image post-processing.According to the problem of image binarization, we adopted the adaptive binarization first remove the shadow again. The main purpose of the above operation is to avoid failure of removing the shadow of QR code image.Is adopted in this paper, in terms of images to remove the shadow in the morphology of corrosion expansion effectively removed the shadow, using adaptive binarization algorithm to reduce the computational complexity of post-processing, binary.In terms of image edge detection and image geometric correction. In this paper, application of expansion and corrosion of morphology in image processing to extract the edge of the target area for straight line has achieved good results, the experiment successfully extracted four edges, got four control points and correcting of the QR code through the projection transformation and linear interpolation.Through the above algorithm, designed the QR code image preprocessing system, the simulation implements the QR code to remove the shadow of the image and getting the final image correction.