Extracting Features On Indonesian Rupiah Notes Using 2DPCA Algorithm For Forged Detection

Abstract

Counterfeit currency nominal value of Rp 100.000,- and Rp 50.000,- is the highest circulating money. Thus are the reason why Bank Indonesia forming a central database called Bank Indonesia Conterfeit Analysis Center (BI-CAC). Indonesian government socialize how to recognize counterfeit money for the community as a preventative measure, the 3D method; Dilihat (seen) , Diraba (touched) and Diterawang. The principle of "seen" is a method that will be used in the pattern recognition / image for visual perception as objects that can be seen by the human eye has an important role. The concept of "seen" on the 3D method for the introduction of the authenticity of the Indonesian currency, the image is done by the introduction of the currency and digital image processing to detect authenticity. The identification of Rupiah paper currency using feature extraction method. This method provides another alternative in the process of feature extraction on Rupiah recognition system that can detect counterfeit money accurately and quickly