TRAFIC SIGN DETECTION AND RECOGNITION IN REAL TIME ON MOBILE DEVICES
An automatic traffic sign recognition system localizes road signs from images captured by an onboard camera of a vehicle and determine what road signs depicted. Such systems may support the driver on the road, be part of the self-driving cars or advanced driver assistance systems. This paper proposes an approach for solving traffic sign recognition problem using deep learning methods adopted to mobile devices with low power consumption. The approach consists of two consecutive stages: detection of a traffic sign and recognition of a class of the detected sign. Data for analysis were taken from three open sets of images. In order to analyze the effectiveness of the solution obtained, the results achieved were compared with the results of well-known approaches to object detection based on the use of deep convolutional neural networks. The results showed that the proposed algorithm provides the best recognition quality for all used data sets, as well as the highest recognition rate.