EyeBill-PH: A Machine Vision of Assistive Philippine Bill Recognition Device for Visually Impaired

• Published in: 2020 11th IEEE Control and System Graduate Research Colloquium (ICSGRC) pp. 312 - 317
• Main Authors: Alon, Alvin Sarraga, Dellosa, Rhowel M., Pilueta, Nino U., Grimaldo, Honeylet D., Manansala, Estrelita T.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2020
• Subjects: bill recognition; deep learning; machine vision; raspberry pi; visually impaired
• DOI: 10.1109/ICSGRC49013.2020.9232557

The value of money can be quickly grasped by the fact that virtually all economic, social, and other tasks are carried out and done using money. With dramatic shifts in global growth and other total human needs, the value of money is rising day after day. Money is an important asset that will allow you to run your life. The exchange of goods for products is an older custom, and you cannot buy something you want without any money. It's straightforward to use money, you just have to glance at the currency instantly, pull the appropriate sum of cash out, and that's it. But that may become a challenging job for those who cannot see. Among the most significant issues facing visually impaired people is the identification of money, particularly for paper currency. In this study, it focuses on this problem and is based on a machine vision technique called object detection. The study used Raspberry Pi 4 as a microcontroller, Pi Camera as its capturing device, and a speaker for audio in announcing the detected bill. EyeBill-PH has been done with an overall testing accuracy of 86.3%.