摘要
提出一种基于小波变换与分形维数的车牌汉字识别方法。对字符图像进行预处理和小波变换,应用改进的微分盒维法计算图像分形盒维值,并构造特征向量,利用支持向量机分类器对字符进行分类与识别。实验结果表明,该方法对模糊字符的识别具有鲁棒性,可提高汉字识别率。
Aiming at the problems of the character recognition for degraded license plates,a novel recognition method for Chinese character of license plate based on wavelet transform and fractal dimension is proposed in this paper.The image pre-processing and wavelet transform technologies are applied to the character images.An shifting differential box-counting approach（SDBC） is used to compute fractal box-counting of the images and gain the feature vector.Support Vector Machine（SVM） is adopted to design the classifier for recognizing the chinese characters.Experimental results show that the proposed method is robust in dealing with blurred character images,and it can improve the recognition rate of Chinese characters.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第22期137-138,共2页
Computer Engineering
基金
辽宁省教育厅高等学校科研基金资助项目(L2010232)
关键词
汉字识别
特征提取
小波变换
分形维数
支持向量机
Chinese character recognition
feature extraction
wavelet transform
fractal dimension
Support Vector Machine（SVM）
