Convolutional Neural Network Based Attentive Model for Vehicle License Plate Identification

With the popularity of personal vehicles today, the management of traffic activities is becoming increasingly difficult. Since then, the detection of the right people, the right errors to sanction have become an important challenge to be solved. Therefore, we propose to develop a license plate recognition algorithm to partially solve this problem. The original algorithm will only recognize one license plate per frame. However, as we go further, we will aim to detect multiple license plates at the same time in the frame. Our aim is to apply deep neural network to detection and recognize a license plate in the frame. The proposed method here consists of three main parts: License Plate Detection by Yolo technical, License Plate Segmentation by traditional methodology, and License Plate Recognition by proposed CNN based attention mechanism. The proposed system has achieved 99.21% accuracy in the validation dataset. Our proposed DNN implements the entire identification system including software and hardware in real applications of the mobile with high expansion value.