Machine Learning-based Currency Information Retrieval for Aiding the Visually Impaired People
Blurriness detection; Classification; Counterfeit currency detection; Currency recognition; Deep Learning
Paper currency is one of the most in-demand and long-established payment modes across the globe. People suffering from visual disabilities often face difficulties while handling paper currencies. Over the years, assisting technology has been rekindling itself to serve the aged and disabled person more aptly. Image processing methods and other sophisticated technologies, like Artificial Intelligence, Deep Learning, etc., can be employed to identify banknotes and fetch other valuable pieces of information from them. This paper proposes a framework that focuses on an integrated approach to retrieving data from the paper currency's uploaded image. The current version of the framework focuses on identifying the authenticity of the paper currency and classifying it according to its value. This work is an initiative to help visually impaired people to use paper currencies without assistance from other individuals and support them in living independently. 2021 IEEE.
Chatterjee K.; Obaidat M.S.; Samanta D.; Hafizul Islam S.K.; Joseph N.P.
Proceedings of the International Conference on Computer, Information, and Telecommunication Systems, CITS 2021
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/CITS52676.2021.9618567 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123797222&doi=10.1109%2fCITS52676.2021.9618567&partnerID=40&md5=dbf1890cbfde12c3e4f64cb093f75052
Chatterjee K., CHRIST (Deemed to Be) University, Department of Computer Science, Karnataka, Bangalore, India; Obaidat M.S., University of Sharjah, College of Computing and Informatics, Sharjah, 27272, United Arab Emirates; Samanta D., CHRIST (Deemed to Be) University, Department of Computer Science, Karnataka, Bangalore, India; Hafizul Islam S.K., Indian Institute of Information Technology, Department of CSE, West Bengal, Kalyani, 741235, India; Joseph N.P., CHRIST (Deemed to Be) University, Department of Computer Science, Karnataka, Bangalore, India