This research is aimed to colaborate digital image processing and neural network using Linear Vector Quantization (LVQ) method to make a money counterfeit system detection. The input image of the system is the dancer object image of Rp. 50.000,- money fluorescend by ultraviolet light. The acquisition data was taken from conventional banks. The LVQ method was used to recognize whether the money being recognized is conterfeit or not. The coding was carried out using visual programme language. The size of the dancer recognized object was in 90x114 px, and its RGB was extracted. The experimental results show that the system has an accuracy 100% of detecting 20 real test case data, as well as detecting 14 simulated test case data. The simulated case data was generated by varying the brightness of the data image. The real test case data contains of 10 counterfeit money and 10 original money. The simulated case data contains of 3 original money and 11 counterfeit money.
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