文章基本信息

标题：Multimodal Biometric Methods to Avoid Authentication Problems
本地全文：下载
作者：Dr.K.P.Kaliyamurthie ; Sundararajan.M ; Arulselvi S 等
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2015
卷号：4
期号：7
页码：6261
DOI：10.15680/IJIRSET.2015.0407271
出版社：S&S Publications
摘要：Multimodal biometric methods use different fusio n techniques to avoid authentication problems such as noisy sensors data, non- universality, and unacceptable error rates. Fusion methods have been proposed in different levels such as feature level and classification level. In this paper, we propose two multimodal biometric authentication methods using ear and finger knuckle (FK) images. A method based on fusion of images of ear and FK before the feature level is proposed, thus there is no information lost. A multi -level fusion method at image and classification levels is also proposed. The features are extracted from the fused images using different classifiers and then co mbine the outputs of the classifiers in the abstract, rank, and score levels of fusion. Experimental results show that the proposed authentication methods increase the recognition rate compared to the state-of- the-art methods.
关键词：Biometric Data; Authentication Methods; Ear and FingerK nuckleImages;ImageFusion