Mobile robot action based on QR code identification

Nowadays, with the developing of the computer science, computer vision is widely used in many areas. It is still a major problem about feature recognition in complex background and uneven intensity of light environment. Some researchers have already achieved in particular conditions. With the robot stepping into family, it is necessary to conduct in-depth study about feature recognition and access to information in complex indoor environmental conditions. In this paper, we present a fast identification approach for QR code in the indoor environment with normal light intensity. In the process of image feature recognition, it is very difficult for the edge while recognizing the slope image. Therefore, we use vector method to express the color characteristics in the image, and use the square minimum method to determine the edge lines of the pattern. In addition, linear scale transformation makes the image pattern more suitable for standard grids, which can correct the tiny sampling error. Besides, in the experiment of emulation process, we add a colored periphery features to positioning the image. It can be captured clearly due to the special colored background and behave well in the distance of 0.5m to 2m. Using an 860-pixel distance camera, the QR code pattern can be captured easily and identified effectively. A feedback control planar mobile robot is used as a platform to verify the identification method. After the robot heading to the front of the QR code pattern about 0.5m, the data of the sample image can be scanned and read accurately. The experiment results show that the approach is feasible and effective.