Skip to main content

Banking Deposit Number Recognition Using Neural Network

  • Conference paper
Software Engineering and Computer Systems (ICSECS 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 179))

Included in the following conference series:

  • 1578 Accesses

Abstract

During normal cash deposit process, the bank customer will fill in the account number, amount of cash and name of the account holder at the bank in slip, then key in the account number and amount manually into the computer. If there are numbers of customer at one time, the process will take times and sometime the banker will make errors during reading or keying the data. The recognition process was executed using integration of Artificial Intelligent techniques: image preprocessing and Neural Network. Image processing techniques were used to extract the written character on the slip. After that, the extracted characters were passed to the recognition phase, where Neural Network will identify the input character patterns. Results: We tested the proposed method using 40 cash deposit slip written with numbers to be tested. 3 neural networks with 40, 50 and 60 training data particularly were used to test the success rate of recognition. Through experiment, the proposed system had successfully recognizes at least 90% of the written character on cash deposit slips. Using the proposed approach, we developed an automatic banking deposit number recognition system which is able to recognize the handwritten account number and amount number on the cash deposit slip and thus automate the cash deposit process at bank counter.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Smith, S.E.: What is a deposit slip (2008), http://www.wisegeek.com/what-is-a-deposit-slip.htm

  2. Yi, X., Hong, Y.: Text region extraction in a document image based on the Delaunay tessellation. Pattern Recognition, vol. 36, 799–809 (2003), doi:10.1016/S0031-3203(02)00082-1.

    Google Scholar 

  3. Prasad, J.R., Kulkarni, U.V.: Trends in Handwriting RecognitionThird. In: International Conference on Emerging Trends in Engineering and Technology, November 19-21, p. 491 (2010), doi:10.1109/ICETET.2010.92. Dsfdsf

    Google Scholar 

  4. Xian, W., Govindraju, V., Srihari, S.: Holistic Recognition of Touching Digits. In: Advances in Handwriting Recognition, pp. 359–369. World Scientific Publications, Singapore (1999)

    Google Scholar 

  5. Nishiwaki, D., Yamada, K.: New Numeral String Recognition Method Using Character Touching Type Verification. In: Advances in Handwriting Recognition, pp. 416–425. World Scientific Publications, Singapore (1999)

    Chapter  Google Scholar 

  6. Lee, S.W.: Advances in Handwriting Recognition. Series in Machine Perception Artificial Intelligence, vol. 34. Word Scientific Publications, Singapore (1998), ISBN- 981-02-3715-4

    Google Scholar 

  7. Faruq, A.A., Omar, A.: Handwritten Indian Numerials Recognition System using Probabilistic Neural Network. Advanced Eng. Inform. 18, 9–16 (2004), doi:10.1016/j.aei.2004.02.001.

    Article  Google Scholar 

  8. Heaton, J.: Introduction to Neural Networks for Java, 2nd edn., p. 380. Heaton Research Inc. (2005) ISBN: 978-0977320608

    Google Scholar 

  9. Heaton, J.: A Feed Forward Neural Network (2008), http://www.heatonresearch.com/articles/5/page2.html

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Yusob, B., Muhamad Zain, J., Wan Hussin, W.M.S., Lim, C.S. (2011). Banking Deposit Number Recognition Using Neural Network. In: Mohamad Zain, J., Wan Mohd, W.M.b., El-Qawasmeh, E. (eds) Software Engineering and Computer Systems. ICSECS 2011. Communications in Computer and Information Science, vol 179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22170-5_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-22170-5_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22169-9

  • Online ISBN: 978-3-642-22170-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics