Ship License Plate Detection and Recognition Algorithm Based on YOLOv8 and Improved CRNN

With the increasing frequency of inland waterway shipping, effective management and monitoring of ships have become particularly important. As the only identification of a ship, the ship license plate is of great significance in the fields of lock management, inland waterway ship dispatching and port management. However, due to factors such as ship motion, water reflection, different sizes of ship plates and complex background, the detection and recognition of ship plates face many challenges. To this end, this paper proposes an end-to-end ship plate detection and recognition algorithm based on YOLOv8 and Improved Convolutional Recurrent Neural Network (YOLOv8-ICR). In the part of license plate detection, we use the YOLOv8 algorithm as the main body, combined with the CSPDarknet structure improvement, the introduction of the attention mechanism, the use of adaptive anchor boxes and hybrid loss functions, etc., to enhance the model's ability to quickly and accurately detect the license plate area in complex backgrounds. In the part of ship license plate recognition, we improved the CRNN algorithm. We used a deeper convolutional neural network structure to improve the feature extraction capability, and adopted a bidirectional long short-term memory network (BiLSTM) to capture the context information of the character sequence effectively and to improve the recognition accuracy further. Finally, the LeakyReLU activation function was used instead of the traditional ReLU activation function to solve the problem that the ReLU function causes neurons to not learn in the negative interval, thereby improving the recognition accuracy of the character sequence. Experimental results show that the proposed YOLOv8 and improved CRNN based ship license plate detection and recognition model has achieved excellent performance on the Guangxi Xijiang ship license plate dataset. This method can not only quickly and accurately locate the ship license plate position, but also read the digital and letter information on the ship license plate with high precision, providing strong technical support for inland waterway shipping management.