Sunday 21st of January 2018

Biometric Authentication Methods Based on Ear and Finger Knuckle Images

Abdelhameed Ibrahim

Multimodal biometric methods use different fusion 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 combine 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.

Keywords: Biometric Data, Authentication Methods, Ear and Finger Knuckle Images, Image Fusion

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Abdelhameed Ibrahim
Abdelhameed Ibrahim was born in Mansoura city, Egypt, in 1979. He attended the Faculty of Engineering, Mansoura University, in Mansoura, where he received Bachelor and Master Degrees in Engineering from the electronics (Computers Engineering and Systems) department in 2001 and 2005, respectively. He was with the Faculty of Engineering, Mansoura University, from 2001 through 2007. In April 2007, he joined the Graduate School of Advanced Integration Science, Faculty of Engineering, Chiba University, Japan, as a doctor student. He received Ph.D. Degree in Engineering in 2011. His research interests are in the fields of computer vision and pattern recognition, with special interest in material classification based on reflectance information.

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