计算机工程与应用2025，Vol.61Issue(4)：230-240,11.DOI:10.3778/j.issn.1002-8331.2309-0283
改进YOLOX的轻量级多方向车牌检测算法
Improved Lightweight Multi-Directional License Plate Detection Algorithm of YOLOX
摘要
Abstract
In response to the problems of the existing license plate detection algorithms in complex environments,such as poor performance in detecting multi-directional license plates,low real-time capabilities,and excessive model parameters and computational complexity,a lightweight multi-directional license plate detection algorithm based on YOLOX is pro-posed.By adjusting the number of residual components and using a combination of large convolution kernels and depth-wise separable convolutions,the parameter count of the backbone network is reduced.A channel attention mechanism is introduced to effectively extract channel interaction information and reduce noise interference.The feature fusion network is lightweighted by using depthwise separable convolutions and adjusting the expansion ratio.A rotation decoupling head is designed,and an angle prediction branch is added to enable more accurate prediction of the rotation bounding boxes of multi-directional license plates.The rotation IoU loss is used instead of the horizontal IoU loss to improve detection accu-racy.Experimental results on the CCPD dataset show that the improved algorithm has the parameter count and computa-tional complexity of 2.38 million and 12.97 GFLOPs,respectively,which are reduced by 45%and 33%compared to YOLOX-tiny.The detection accuracy AP70 is 94.9%,and the detection frame rate is 76.6 FPS.The improved license plate detection model can detect multi-directional license plates in real-time while maintaining high accuracy.关键词
深度学习/轻量化/YOLOX/目标检测/注意力机制Key words
deep learning/lightweight/YOLOX/object detection/attention mechanism分类
信息技术与安全科学引用本文复制引用
雷景生,章志豪,钱小鸿,王巍然,杨胜英..改进YOLOX的轻量级多方向车牌检测算法[J].计算机工程与应用,2025,61(4):230-240,11.基金项目
浙江省"尖兵""领雁"科技计划项目(2024C01109) （2024C01109）
基于标签技术的电网信息项目智能管理系统研究及应用(066700KK52180021). （066700KK52180021）
