TY - GEN
T1 - An Intelligent Banknote Recognition System by using Machine Learning with Assistive Technology for Visually Impaired People
AU - Ng, Sin Chun
AU - Kwok, Chok Pang
AU - Chung, Sin Hang
AU - Leung, Yuen Yan
AU - Pang, Hoi Shan
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9
Y1 - 2020/9
N2 - Hong Kong Dollar is the main currency used in Hong Kong. Hong Kong banknotes are issued by three commercial banks, namely Hongkong and Shanghai Banking Corporation (HSBC), Standard Chartered Bank, and Bank of China. People can typically differentiate the different denominations of coins and banknotes easily by their characteristics. For visually impaired, they can simply determine the values of coins by tactile sense due to the unique size and shape of each type of coin. However, it will be difficult for visually impaired to differentiate different denominations of different types of banknotes. Although the size of each banknote category is different, and it contains characteristics like high-tactility numeral at top left-hand corner, braille and tactile lines at the bottom left-hand corner of the banknote. These features can be used for recognition when the banknote is pretty new. When the banknote becomes old, the features will be unapparent, so visually impaired are hard to confirm the values of the banknotes. Moreover, cheating in purchasing will be much easier in paying the amounts or collecting the change during monetary transactions. In this paper, a tailor-made intelligent banknote recognition system is developed by applying machine learning with assistive technology for visually impaired to determine the denominations of the banknotes effectively and efficiently. The application can be used in a smartphone with sound and vibration to facilitate the daily monetary consumption of the visually impaired people.
AB - Hong Kong Dollar is the main currency used in Hong Kong. Hong Kong banknotes are issued by three commercial banks, namely Hongkong and Shanghai Banking Corporation (HSBC), Standard Chartered Bank, and Bank of China. People can typically differentiate the different denominations of coins and banknotes easily by their characteristics. For visually impaired, they can simply determine the values of coins by tactile sense due to the unique size and shape of each type of coin. However, it will be difficult for visually impaired to differentiate different denominations of different types of banknotes. Although the size of each banknote category is different, and it contains characteristics like high-tactility numeral at top left-hand corner, braille and tactile lines at the bottom left-hand corner of the banknote. These features can be used for recognition when the banknote is pretty new. When the banknote becomes old, the features will be unapparent, so visually impaired are hard to confirm the values of the banknotes. Moreover, cheating in purchasing will be much easier in paying the amounts or collecting the change during monetary transactions. In this paper, a tailor-made intelligent banknote recognition system is developed by applying machine learning with assistive technology for visually impaired to determine the denominations of the banknotes effectively and efficiently. The application can be used in a smartphone with sound and vibration to facilitate the daily monetary consumption of the visually impaired people.
KW - assistive technology
KW - banknote recognition
KW - machine learning
KW - visually impaired
UR - http://www.scopus.com/inward/record.url?scp=85093958499&partnerID=8YFLogxK
U2 - 10.1109/ICIST49303.2020.9202087
DO - 10.1109/ICIST49303.2020.9202087
M3 - Conference contribution
AN - SCOPUS:85093958499
T3 - 10th International Conference on Information Science and Technology, ICIST 2020
SP - 185
EP - 193
BT - 10th International Conference on Information Science and Technology, ICIST 2020
T2 - 10th International Conference on Information Science and Technology, ICIST 2020
Y2 - 9 September 2020 through 15 September 2020
ER -