One- and Five-Ringgit Malaysia banknotes reader with counterfeit detection for visually impaired person using...

Area of Science:

• Computer Science
• Engineering
• Assistive Technology

Background:

• Visually impaired individuals face significant challenges in daily financial transactions, particularly with identifying and verifying banknotes.
• Existing banknote readers for the visually impaired in Malaysia primarily focus on value recognition, lacking crucial counterfeit detection capabilities.
• This gap necessitates a more comprehensive solution to prevent financial losses due to counterfeit currency.

Purpose of the Study:

• To develop an advanced handheld banknote reader for visually impaired users.
• To enable accurate recognition of Malaysian Ringgit banknote values (1 and 5 Ringgit).
• To integrate counterfeit detection features, safeguarding users from financial fraud.

Main Methods:

• Utilized a backlight mechanism and image processing techniques for banknote analysis.
• Employed a Raspberry Pi controller to process captured banknote images and extract security features.
• Developed an image processing algorithm to identify key security features such as see-thru windows and watermarks.

Main Results:

• The developed system successfully recognized Malaysian Ringgit banknote values and detected counterfeit notes in experimental trials.
• The image processing algorithm accurately identified critical security features for authentication.
• Performance analysis using a confusion matrix demonstrated the system's effectiveness, with a focus on minimizing false positives and negatives.

Conclusions:

• The proposed banknote reader effectively aids visually impaired individuals in identifying Malaysian Ringgit banknotes and detecting counterfeits.
• The integration of value recognition and counterfeit detection enhances financial security for the visually impaired community.
• This assistive technology represents a significant advancement in empowering visually impaired persons in financial dealings.