CAJ | 학술논문

掌纹识别是一门新兴的生物特征识别技术。提出基于分块双向二维主成分分析（M（2D）2 PCA）和模糊分类的掌纹识别方法。该算法利用M（2D）2 PCA提取掌纹的局部特征，并利用模糊分类策略。这种方法可以有效提取掌纹的局部特征，并且直接对子图像矩阵进行特征抽取，能够精确计算协方差矩阵的特征向量；分类阶段引入模糊理论，应用于掌纹识别问题。最后使用北京交通大学掌纹数据库进行识别实验，结果表明，该方法可得到更高的识别率和更少的识别时间。
장문식별시일문신흥적생물특정식별기술。제출기우분괴쌍향이유주성분분석（M（2D）2 PCA）화모호분류적장문식별방법。해산법이용M（2D）2 PCA제취장문적국부특정，병이용모호분류책략。저충방법가이유효제취장문적국부특정，병차직접대자도상구진진행특정추취，능구정학계산협방차구진적특정향량；분류계단인입모호이론，응용우장문식별문제。최후사용북경교통대학장문수거고진행식별실험，결과표명，해방법가득도경고적식별솔화경소적식별시간。
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.