@article{digilib22545,
          volume = {Vol.1},
          number = {No. 2},
           month = {February},
          author = {Dewanto Harjunowibowo and Sri Hartati and Aris Budianto},
           title = {A Counterfeit Paper Currency Recognition System
Using LVQ based on UV Light},
       publisher = {Fakultas Sains dan Teknologi},
            year = {2012},
         journal = {IJID (International Journal on Informatics for Development)},
           pages = {9--13},
        keywords = {detection system, counterfeit paper
currency, neural network, LVQ, digital image processing},
             url = {https://digilib.uin-suka.ac.id/id/eprint/22545/},
        abstract = {This research is aimed to test a paper currency
counterfeit detection system based on Linear Vector
Quantization (LVQ) Neural Network. The input image of the
system is the dancer object image of paper currency Rp. 50.000,-
fluorescent by ultraviolet light. The image of paper currency data
was taken from conventional banks. The LVQ method is used to
recognize whether the paper currency being tested is counterfeit
or not. The coding was carried out using visual programming
language. The feature size of the dancer tested object is 114x90
px and the RGBHSI was extracted as the input for LVQ. The
experimental results show that the system has an accuracy 100\%
of detecting 20 real test case data, and 96\% of detecting 22
simulated test case data. The simulated case data was generated
by varying the brightness of the image data. The real test case
data contains of 10 counterfeit paper currency and 10 original
paper currency. The simulated case data contains of 11 original
paper currency and 11 counterfeit paper currency. The best
setting for the system is Learning Rate = 0.01 and MaxEpoh =
10.
Keywords-CRM 2.0; detection system, counterfeit paper
currency, neural network, LVQ, digital image processing}
}