计算机应用与软件Issue(4)：149-152,4.DOI:10.3969/j.issn.1000-386x.2015.04.036
分块双向二维主成分分析与模糊分类的掌纹识别
PALMPRINT RECOGNITION BASED ON BLOCKING BI-DIRECTIONAL TWO-DIMENSIONAL PRINCIPAL COMPONENT ANALYSIS AND FUZZY CLASSIFICATION
摘要
Abstract
Palmprint recognition is an emerging biological feature recognition technology.We present a palmprint recognition method, which is based on blocking bi-directional two-dimensional principal component analysis (M(2D)2PCA)and fuzzy classification.The algorithm uses M(2D)2 PCA to extract palmprint local features,and uses fuzzy classification strategy as well.This method can effectively extract palmprint local features and directly extracts the feature of sub-image matrix,it can accurately calculate the eigenvectors of covariance matrix;in classification stage it introduces fuzzy theory and applies it to palmprint recognition problem.Finally,we use the palmprint database at Beijing Jiaotong University in recognition experiment.Results show that this method achieves higher recognition rate and less recognition time.关键词
分块/双向二维主成分分析/模糊分类/掌纹识别Key words
Blocking/Bi-directional two-dimensional principal component analysis/Fuzzy classification/Palmprint recognition分类
信息技术与安全科学引用本文复制引用
翟林,潘新,刘霞,郜晓晶,宁丽娜,韩璠..分块双向二维主成分分析与模糊分类的掌纹识别[J].计算机应用与软件,2015,(4):149-152,4.基金项目
内蒙古自然科学基金项目（2012MS0919，2012MS0927）；内蒙古农业大学基础学科科研启动基金项目（JCYJ201201）；内蒙古农业大学创新团队项目（NDPYTD210－9）。 （）
