Authors: Aylar, John Albert F., Chan, Bernard N., and Quiambao, Karla Denise M.

Issue: 2019

Abstract:

Counterfeit currency poses a major economic threat globally. While counterfeit detectors already exist in the market, this research aims to further innovation through a new android application system targeted specifically at detecting fake Philippine 500 and 1000 peso banknotes. These higher denomination bills contain key security features such as concealed values, embossed prints, and optically variable ink which are examined by the application. The app applies image processing techniques including preprocessing, segmentation, color analysis, correlation, convolution, and geometry to automatically analyze banknote images and determine authenticity. By focusing on replicating the detection of security print features unique to the 500 and 1000 peso notes, this mobile solution offers an accessible, efficient, and reliable method to assist the public in identifying fake bills in circulation. The computer vision methodology developed here can also serve as a foundation to build out more advanced counterfeit detection functionalities for further research. Overall, this work pursues the maximization of mobile technology to combat counterfeiting and its detrimental impacts on economic systems.