为了提高车牌上的字符识别准确率，提出一种结合支撑矢量机(SVM)和小波的字符识别方法。
To improve the recognition accuracy of the characters on car license plate, a novel method based on support vector machine (SVM) and wavelet decomposition was proposed.
将最小二乘支持向量机引入到小字符集压印字符识别中。
This paper presents an application of least squares support vector machines in small-set pressed protuberant character recognition.
在字符识别模块，采用了基于支持向量机的字符识别方法。
In the character recognition module, a recognition approach based on support vector machine is applied.
在字符识别部分，提出了在无特征提取情况下基于支持向量机的车牌字符识别方法。
A local projection method is used to segment character. At Last, a License Plate Recognition method based support vector machines is proposed.
在探索手写字符识别的方法上采用了统计学习理论，利用支撑向量机SVM作为基本的识别工具。
Support Vector Machine (SVM) is used as the implementation basis, which is a tool of Statistical Learning Theory (SLT).
在探索手写字符识别的方法上采用了统计学习理论，利用支撑向量机SVM作为基本的识别工具。
Support Vector Machine (SVM) is used as the implementation basis, which is a tool of Statistical Learning Theory (SLT).
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