Counterfeit bill recognition using neural networks

• Main Authors: Biagtan, Marco Giovanni B., Lee, Roderick C., Ong, Benjimen Y.K., Yu, Francis Rainier C.
• Format: text
• Language: English
• Published: Animo Repository 1995
• Subjects: Neural circuitry; Money; Counterfeits and counterfeiting; Imaging systems; Neural networks
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/8525
• Institution: De La Salle University

Neutral networks has gained grounds for its wide of applications. It has been used as a vehicle for adaptively developing functions by training sets of patterns for recognition. With the proper algorithm and training, it can identify different images including genuine from counterfeit bills.Every denomination of authentic peso bills possess certain characteristics which distinguishes it from the counterfeit ones. An example of such a characteristic is the presence of an illuminated image on the bill seen only when exposed under ultraviolet light. This thesis would involve itself in the development of a semi-automated module with an algorithm that would determine the authenticity of Philippine Peso bills by determining if the illuminated numerical image is present or not.The counterfeit bill recognition system will employ a process involving the capturing of the specific images on peso bills under ultraviolet and white lights via the video camera. The images will be digitized and converted into Tagged Image File Format (TIFF) using a Video Blaster card. These images will then be enhanced through an image processing algorithm written in Borland C++ before being used as inputs of the neural networks to determine the authenticity of the bill.