3D Palmprint recognition using Tan and Triggs normalization technique and GIST descriptors
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3D Palmprint recognition using Tan and Triggs normalization technique and GIST descriptors Mourad Chaa 1 & Zahid Akhtar 2 Received: 7 April 2020 / Revised: 7 August 2020 / Accepted: 20 August 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
The 3D palmprint biometric recognition system is being considered as a very promising way to address the limitations of 2D palmprint recognition systems. This paper introduces a novel method for the 3D palmprint recognition based on the Tan and Triggs normalization technique (TT) for the preprocessing data and GIST descriptor for feature extraction. The TT technique can effectively and efficiently eliminate not only the low frequencies containing the undesirable effects of shadows but also high frequencies containing aliasing and noise in 3D palmprint. The holistic feature extraction method has been employed to attain salient characteristics. Finally, for the features matching the cosine Mahalanobis distance has been used for 3D palmprint recognition. The proposed system has been evaluated on publicly available 3D palmprint database of 8000 samples. Experimental analyses show that the proposed method can functionally eradicate the effect of uneven illumination and greatly improve the performance of the recognition system. Moreover, experimental results demonstrate that our method is capable of competing with many existing state-of-the-art 3D palmprint recognition techniques as well as outperforming many others. Keywords 3D palmprint . Tan and Triggs normalization technique . GIST descriptor . Biometric system . PCA + LDA
* Mourad Chaa chaa.mourad@univ–ouargla.dz Zahid Akhtar [email protected]
1
Fac. New information and communication technologies, ELEC Laboratory, University Ouargla, 30,000 Ouargla, Algeria
2
Department of Network and Computer Security, State University of New York Polytechnic Institute, Utica, NY 13502, USA
Multimedia Tools and Applications
1 Introduction Contributions Robust and dependable identity management systems have become an international demand in various fields. In fact, security and privacy have become a delicate problem for citizens, companies and the governments due to large scale information and data theft [13, 14]. Biometrics is a method of identifying individuals from biological characteristics. Nowadays, various biometric traits have been employed such as face, fingerprint, palmprint, DNA, voice and iris 2. The design of a reliable, efficient and resilient biometric identification system still has to go a long way. The identification of the individual is essential to ensure the security of systems and organizations [3, 12]. Identification or recognition systems based on biometrics prove to be potentially effective in order to respond the needs of security. To this end, remarkable efforts have been recently done in emerging identification system, i.e., palmprint based individual recognition model. The conducted researches on palmprint recognition principally concentrate on 2D palmprint traits. They h
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