Research And Application Of QR Code In The Android System

With the development of information society, the bar-code technology has been widely applied in the field of logistics, documents management, security and e-commerce, greatly improving the efficiency of production. Cellphone and2D bar-code are combined into handphone2D barcode. At present, handphone2D barcode has brought great convenience into the people’s lives. However, handphone2D barcode has to face the following problems:first, the quality of the images collected by handphone; second, limited hardware resources. The hardware of cellphone in recent years has been greatly enhanced, but its computing power and storage space compared with the PC is still a wide gap, so handphone2D barcode cannot use too complex image processing algorithms. To solve these problems to promote the use and development of mobile2D barcode technology in China, the research on2D barcode reading on the mobile phone platform has great significance.On the basis of the existing QR Code identify technology and because of mobile platforms with limited hardware resources, the QR code reader is in the problems such as uneven lighting, image distortion, a more reasonable solutions is proposed in this thesis. As for the problem of QR Code image uneven illumination, an improved binarization algorithm based on the background intensity correction is proposed. As for the QR Code image distortion problem, this thesis introduces a geometric correction algorithm based on location, rotation, bilinear transformation and interpolation. Finally, an application of Renren-card is developed by using the algorithm, which contains a complete QR Code encoding and recognition. And in the process of developing, JNI technology is used for optimization and improvement as to the architecture of Android platform. At present, this application can be downloaded on Renren-open-platform.The test results show that the mobile phone can be able to identify QR code by using the algorithm under the case of uneven illumination and image distortion, which meets the time requirements and accuracy requirements for reading2D barcode on the hardware resource-constrained mobile phones.