caa a22 4500 605447314 CHVBK 20210128100131.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s11042-013-1833-x doi (NATIONALLICENCE)springer-10.1007/s11042-013-1833-x An empirical approach for currency identification [Elektronische Daten] [Wei Yan, J. Chambers, A. Garhwal] Currency identification is the application of systematic methods to determine authenticity of questioned currency. However, identification analysis is a difficult task requiring specially trained examiners, the most important challenge is automating the analysis process reducing human labor and time. In this study, an empirical approach for automated currency identification is formulated and a prototype is developed. A two parts feature vector is defined comprised of color features and texture features. Finally the banknote in question is classified by a Feedforward Neural Network (FNN) and a measurement of the similarity between existing samples and suspect banknote is output. Springer Science+Business Media New York, 2014 Currency identification nationallicence Neural network nationallicence Empirical approach nationallicence Yan Wei AUT University, Auckland, New Zealand aut Chambers J. AUT University, Auckland, New Zealand aut Garhwal A. AUT University, Auckland, New Zealand aut Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/13(2015-07-01), 4723-4733 1380-7501 74:13<4723 2015 74 11042 https://doi.org/10.1007/s11042-013-1833-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11042-013-1833-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Yan Wei AUT University, Auckland, New Zealand aut NATIONALLICENCE 700 1- Chambers J. AUT University, Auckland, New Zealand aut NATIONALLICENCE 700 1- Garhwal A. AUT University, Auckland, New Zealand aut NATIONALLICENCE 773 0- Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/13(2015-07-01), 4723-4733 1380-7501 74:13<4723 2015 74 11042