Beschreibung
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. Color and texture feature are used for the classification of an image. This research presents the techniques used for the extraction of feature, identification and classification of counterfeit and genuine bank note. It presented simple method of identification of counterfeit paper banknotes, which automatically using image processing techniques. Color and texture feature of a currency is used for identification. Color descriptor skew, mean and standard deviation is calculated from samples which are checked against the parameter that are previously defined. Texture parameter entropy and correlation are calculated from different set of database image. Matching score below the threshold, input currency image is classified as fake note. Otherwise the currency is genuine. Image processing approach is very useful for classification of different types of currency.
Autorenporträt
Shaurav Lamsal holds a B.E. in Electronics and Communication Engineering, a Msc. in Electronics and Communication Engineering from Tribhuvan University (Kathmandu). He has more than 5 years of Professional experiences in the field of Information Technology in Local bodies of Nepal.Currently he is working in Government of Nepal, Department of IT.
Herstellerkennzeichnung:
OmniScriptum SRL
Str. Armeneasca 28/1, office 1
2012 Chisinau
MD
E-Mail: info@omniscriptum.com
