Street Sign Recognition Algorithm Based on Deep Learning
Jiawei Wang, Cen Chen, Chongwen Wang · 2020
The complex background, uneven illumination and object occlusion have increased the difficulty of scene texts detection. In this paper, we improved the existing object detection algorithm SSD, and made it possible to detect text objects in traffic guidance sign. We used a deep neural network CRNN to identify the text. This network is a combination of Convolution Neural Network and Recurrent Neural Network. At the same time, we proposed a new idea to optimize the detection algorithm through the text recognition result, so that the whole network can be trained end-to-end. According to the experimental results, the detection network achieves 88% mAP on our dataset at 11.6FPS, which has a good recognition effect.