Ataş, Musa2019-11-052019-11-052017-10-20Ataş, Musa. "Hand tremor based biometric recognition using leap motion device." IEEE Access 5 (2017): 23320-23326.2169-3536https://hdl.handle.net/20.500.12604/872In this paper, the applicability of hand tremor-based biometric recognition via leap motion device is investigated. The hypothesis is that the hand tremor is unique for humans and can be utilized as a biometric identification. In order to verify our hypothesis, spatiotemporal hand tremor signals are acquired from subjects. The objective is to establish a live and secure identification system to avoid mimic and cloning of password by attackers. Various feature extraction methods, including statistical, fast Fourier transform, discrete wavelet transform, and 1-D local binary pattern are used. For evaluating recognition performance, Naïve Bayes and Multi-Layer Perceptron are utilized as linear-simple and nonlinear-complex classifiers, respectively. Since the conducted experiments produced promising results (above 95% of classification accuracy rate), it is considered that the proposed approach has the potential to be used as a new biometric identification manner in the field of security.eninfo:eu-repo/semantics/openAccessFeature extraction , Data acquisition , Discrete wavelet transforms , Object recognition , Biometrics (access control) , Authentication , SoftwareArticleQ1WOS:000415170700030Q12-s2.0-85032658809