摘要
为了准确快速的识别车牌,设计并实现了一种基于人工蜂群算法优化支持向量机(ABC-SVM)的车牌识别系统。该系统以STM32单片机为主控,通过控制OV7725摄像头进行车牌图像采集,采用4G无线模块将采集到的车牌图像发送给上位机进行处理识别。上位机利用人工蜂群算法对支持向量机的惩罚系数和核参数进行优化,并结合支持向量机构建车牌字符识别模型。测试结果表明,系统能够准确快速的识别车牌,识别准确率(93.3%)较传统BP神经网络(85.0%)和支持向量机(88.1%)分别提高了8.3%和5.2%。
In order to accurately and quickly recognize the license plate,a license plate recognition system based on ABC-SVM algorithm was designed and implemented in this paper.In this license plate recognition system,the STM32 microcontroller is used as the main controller to control OV7725 camera to collect license plate images,and the collected images are send to the upper computer for further recognition processing through 4 Gwireless module.In the upper computer,the penalty coefficient and the kernel function parameter of support vector machine are optimized by artificial bee colony algorithm,and the license plate character recognition model is setup combined with support vector machine.The test results show that this system can accurately and quickly recognize the license plate,and its recognition accuracy can be increased by 8.3% and 5.2%,reaching 93.3%,while the conventional support vector machine and BP neural network can reach only 85.0% and 88.1%.
作者
刘雪阳
Liu Xueyang(Tongda College,Nanjing University of Posts and Telecommunications,Yangzhou 225127,China)
出处
《电子测量技术》
2018年第24期94-98,共5页
Electronic Measurement Technology
