期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2014
卷号：7
期号：3
页码：347-360
DOI：10.14257/ijsip.2014.7.3.28
出版社：SERSC
摘要：In this paper usefulness of time series based Auto Regressive (AR) modelling technique has been explored for identification of a person. For this purpose, time series is obtained from the contour coordinates of the ear. AR model is fitted to this time series. AR coefficients thus obtained serve as a feature vector. Recognition Rate (RR) has been found by a classifier that is based on Euclidian distance between feature vector of test samples with training samples within itself (intraclass) and with respect to others (interclass). Model has been found invariant to posture, rotation and illumination. RR up to 99% has been obtained. Results have been compared with existing techniques. The results demonstrate the effectiveness of technique for human identification.
关键词：Ear biometrics; Human identification; Time series modelling; AR ; modelling; Recognition
