通信学报2018，Vol.39Issue(12)：40-46,7.DOI:10.11959/j.issn.1000-436x.2018285
四元共空间特征提取算法及其在纸币识别中的应用
Feature extraction algorithm based on quaternion common spatial pattern for banknote recognition
摘要
Abstract
New feature extraction algorithm was proposed based on quaternion common spatial pattern in order to solve the lack of effective description of phase information in the banknote feature extraction and analysis. Firstly, the quaternion matrix was utilized to describe the phase information of the banknote image, and made diagonalization of quaternion composite Hermitian matrix. Secondly, the sample vector was input to the composite quaternion filter. The extracted feature vector was obtained by using the variance of the real part and imaginary part. Finally, the neural network was applied as classifier and the reject class was introduced in the banknote recognition. The experimental results illustrate that the proposed algorithm obtains high recognition rate and meets the real-time requirement of the banknote recognition system. The proposed algorithm has already been applied in a resource-constrained embedded system at the same time.关键词
四元矩阵/共空间模式/特征提取/神经网络/纸币识别Key words
quaternion matrix/ common spatial pattern/ feature extraction/ neural network/ banknote recognition分类
信息技术与安全科学引用本文复制引用
盖杉..四元共空间特征提取算法及其在纸币识别中的应用[J].通信学报,2018,39(12):40-46,7.基金项目
国家自然科学基金资助项目(No.61563037) （No.61563037）
江西省杰出青年基金资助项目(No.20171BCB23057) （No.20171BCB23057）
江西省自然科学基金资助项目(No.20171BAB202018) （No.20171BAB202018）
