中山大学学报（自然科学版）2017，Vol.56Issue(1)：46-52,7.DOI:10.13471/j.cnki.acta.snus.2017.01.008
基于PSO-BP神经网络的车牌号码识别技术
License plate recognition technology based on PSO-B P neural network
摘要
Abstract
BP neural network has been successfully applied in many fields,such as license plate recog-nition,however the general method of BP neural network is likely to fall into local optimum rather than converge to the global optimum,so its performance of recognition is not very satisfied.In order to avoid this situation,a license plate number recognition technology method is proposed based on PSO-BP neural network.The key of this method is to build an 8-25-1 BP neural network with 8 pixel rate features as its input vector firstly,and then use particle swarm optimization (PSO)algorithm to optimize the weights and thresholds of the BP neural network to get the best fitness value of global searching.By using 300 pair license plate images some with the different illumination and the stained parts,the simulation result indicates that the algorithm we mentioned comparing with the traditional template matching algorithm and general BP algorithm has the certain application value with the advantage of less output errors,global fast convergence,and high recognition rate.关键词
BP神经网络/粒子群算法 (PSO)/PSO-BP神经网络/车牌识别Key words
BP neural network/PSO/PSO-BP neural network/vehicle license plate recognition分类
计算机与自动化引用本文复制引用
吴志攀,赵跃龙,罗中良,杜华英..基于PSO-BP神经网络的车牌号码识别技术[J].中山大学学报（自然科学版）,2017,56(1):46-52,7.基金项目
国家自然科学基金（61572200）；广东省高等学校教学质量与改革工程本科类项目（［2013］113号－113）；惠州市科技计划项目（2014－01）；惠州城市职业学院课题 （）
