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All Journal Proceeding of the Electrical Engineering Computer Science and Informatics
Rosihan Ariyuana, Rosihan
Sebelas Maret University
Computer Science & IT Electrical & Electronics Engineering

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Pattern Recognition on Paper Currency’s Feature Using LVQ Algorithm Harjunowibowo, Dewanto; Hartati, Sri; Ariyuana, Rosihan; Budianto, Aris
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 2: EECSI 2015
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.2.533

Abstract

This research is aimed to test the originality of paper currency using detection system based on Linear Vector X1 Quantization (LVQ) Neural Network method. The input image of the system is the “dancer” object image of paper currency Rp. 50.000,- fluorescent by ultraviolet light. The coding was carried out using visual programming language. The feature’s size of the dancer tested object is 114x90 px and the Red-Green-Blue-Hue- X2 Saturation-Intensity (RGBHSI) values were extracted as the input for LVQ. The experimental result shows that the system has an accuracy 100% of detecting 20 real test case data, and 96% of detecting 22 simulated test case data.
Co-Authors Aris Budianto, Aris Dewanto Harjunowibowo Sri Hartati