Multi-structural QR Code Correction And Recognition

QR-code correction recognition technology is a process of extracting information QR code including using mobile devices to scan QR image on the article. Because in our daily life QR codes are often found in the irregular object cans, bags, cups, etc., So QR code acquisition process will be affected by many factors. Such as geometric distortion caused by the camera angle, QR code generating distorted perspective distortion, etc. So that we cannot correctly identify the QR code, which limits the further promotion of QR codes.Due to so many surfaces where the diversity of each regional variations may exist differences in the deformation QR Code, such as distortions and angles. Coordinate mapping parameters to select complex, which becomes the biggest difficulty to be corrected. Since the traditional QR code recognition methods fail to fulfill the recognition task on multi-structural deformation deformed QR code cases, this paper presents a novel QR code recognition algorithm based on extreme learning machine. In this method, Euclidean distance of feature points are calculated as deformation characteristics. And employed Extreme learning machine to classify the deformation type. It determined the transform coefficients of each type, which were used for coordinates mapping. Then obtained real coordinates by perspective mapping with different transform coefficients, thus the code were reconstructed. Experimental results demonstrate that our proposed method holds a satisfactory performance on both of recognition rate and time consuming.Finally, we compared the use of multiple sets of data on the characteristics of a learning QR Code classification algorithms and a variety of distortion correction algorithms. Experimental results show that, ELM classification algorithm for multi-structural deformation QR code have a good classification accuracy and feature extraction effect, and the structure of correction algorithm based on multiple classifications ELM QR Code not only improve the accuracy of the correction on the surface, but also improve the speed of the surface deformation and the correction plane deformation QR codes.