Automating Data Entry Forms for Banks Using OCR and CNN

Authors

  • Maithilee Vaidya  Department of Computer Engineering, Sinhgad Institute of Technology and Science, Narhe, Pune, Maharashtra, India
  • Praveen Kumar Rule  Department of Computer Engineering, Sinhgad Institute of Technology and Science, Narhe, Pune, Maharashtra, India
  • Hitesh Kumar  Department of Computer Engineering, Sinhgad Institute of Technology and Science, Narhe, Pune, Maharashtra, India
  • Akansha Jain  Department of Computer Engineering, Sinhgad Institute of Technology and Science, Narhe, Pune, Maharashtra, India
  • Prof. Asmita R. Kamble  Department of Computer Engineering, Sinhgad Institute of Technology and Science, Narhe, Pune, Maharashtra, India

DOI:

https://doi.org//10.32628/CSEIT195387

Keywords:

OCR engines, Preprocessing, Row and character segmentation, Otsu's thresholding Techniques

Abstract

Digitalization of money transfer is a must in the present situation of banking operations. Clients have a variety of ways to carry out transactions, such as credit, wiring money, and so forth. However, depositing cash requires the physical presence of the depositor at the bank, and cashier needs to enroll the transaction into the system, which slows down the rate of money deposit and teller's activity. To accelerate the process, banks around the world have to adapt and construct guidelines for a digital deposit. To accurately digitize and transmit deposit slip information from smartphones to the bank, a scheme called 'Automating Data Entry Forms for Banks Using OCR and CNN'. The deposit slip scanner algorithm is based on input from the Smartphone camera.

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Published

2019-06-30

Issue

Section

Research Articles

How to Cite

[1]
Maithilee Vaidya, Praveen Kumar Rule, Hitesh Kumar, Akansha Jain, Prof. Asmita R. Kamble, " Automating Data Entry Forms for Banks Using OCR and CNN, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 3, pp.326-331, May-June-2019. Available at doi : https://doi.org/10.32628/CSEIT195387