Deep Learning Based Indian Currency Detection for Visually Challenged using VGG16
Nijil Raj N1, Anandu S Ram2, Aneeta Binoo Joseph3, Shabna S4
1Dr. Nijil Raj N, Prof. and Head, Department of Computer Science and Engineering, Younus College of Engineering and Technology, Kollam, Kerala, India.
2Anandu S Ram, B.Tech Student, Department of Computer Science and Engineering, Younus College of Engineering and Technology, Kollam, Kerala, India.
3Aneeta Binoo Joseph, B.Tech Student, Department of Computer Science and Engineering, Younus College of Engineering and Technology, Kollam, Kerala, India.
4Shabna S, B.Tech Student, Department of Computer Science and Engi- neering, Younus College of Engineering and Technology, Kollam, Kerala, India.
Manuscript received on July 21, 2020. | Revised Manuscript received on July 24, 2020. | Manuscript published on July 30, 2020. | PP: 969-972 | Volume-9 Issue-2, July 2020. | Retrieval Number: B3955079220/2020©BEIESP | DOI: 10.35940/ijrte.B3955.079220
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Banknote recognition is a major problem faced by visually Challenged people. So we propose a system to help the visually Challenged people to identify the different types of Indian currencies through deep learning technique. In our proposed project, bank notes with different positions are directly fed into VGG 16, a pretrained model of convolution neural network which extracts deep features. From our work the visually impaired people will be able to recognize different types if Indian Currencies.
Keywords: Deep Learning, VGG16.