摘要
车牌定位是汽车牌照自动识别系统中的关键步骤。对车牌定位文体进行研究,提出一种基于支持向量机的定位方法。首先将图像分割为N×N大小的子块,提取每个子块的灰度特征,训练SVM分类器;然后用训练好的分类器进行牌照子块和非牌照子块的分类,再使用数学形态学滤波和区域合并;最后运用投影方法定位牌照区域。实验结果表明,该方法能正确定位牌照区域。
Locating the vehicle license plate plays an important role in the vehicle License Plate Automatic Recognition （LPR） system. An approach based on Support Veetor Machine（SVM） is presented in this paper. First the car image is seg- mented into many N×N sub-blocks, and the gray level value features are exacted from each sub-block and fed to SVM. Then the training SVM is used to classify each pixel into two classes：plate and no-plate, and a morphological filter is applied to merge candidate regions and remove noise. Finally projective algorithm is applied to get plate area in the image. The experiment results show this algorithm is effective.
出处
《现代电子技术》
2008年第9期184-186,共3页
Modern Electronics Technique
关键词
车牌定位
支持向量机
纹理分类
LPR
license plate location
support vector machine
texture classification
LPR
