基于支持向量机的人民币纸币序列号识别方法

Serial Number Identification of RMB Banknote Based on Support Vector Machine

实现了人民币图像预处理和序列号识别,主要研究了统计学习理论中支持向量机的次序最小优化算法,并将其构建的支持向量机用于序列号识别,解决了人民币序列号识别中小样本、非线性和高维模式识别问题.实验结果显示,与简单的BP神经网络相比,这种支持向量机货币识别方法具有较高的可实现性和识别精度.

RMB image pre-processing and serial number identification are achieved. The sequential minimal optimization algorithm of support vector machine （SVM） in statistical learning theory is mainly studied. The support vector machine is used in serial number identification, and it solves the problems of seared samples, nonlinearity and high dimensions in serial number identification on RMB banknote. The experimental result indicates that this money recognition method based on SVM has higher feasibility and identification precision than the simple BP （backpropagation） neural network.