This paper proposed a method based on Faster R-CNN algorithm to locate and recognize Chinese license plate. Faster R-CNN is composed by Region Proposal Network (RPN) and fast R-CNN. To make Faster R-CNN locate and recognize license plate more effective, we optimize the training process. To validate performance of the proposed method, two datasets (standard dataset and real scene dataset) are created. Faster R-CNN with three different model are used. The experimental results show that the proposed method achieve better performance contrasting six traditional methods. In standard dataset (simple situation), three modes achieve similar recognition results. However, in real scene dataset, more deeper model achieve better recognition performance.
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