Skip to main content

Bank Cheque Validation Using Image Processing

  • Conference paper
  • First Online:
Advanced Informatics for Computing Research (ICAICR 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1075))

Abstract

Bank cheques, as documents issued by banks can be used as a form of bills capable of monetary exchange, allowing a payee a certain sum of money from the account of drawer. However, due to many fraudulent practices and a need of faster cheque clearance, there had been advances in the process of cheque clearance. Consequently, to aid the process of cheque validation this research work focuses on implementing image processing techniques such as OCR, ANN and Deep Learning to extract key parameters essential for cheque validation. These techniques can be used in sequential manner to automate the task of cheque validation. For extracting machine typographic information Optical Character Recognition is used. Whereas, for the handwritten characters we have used CNN trained using MNIST dataset. The accuracy achieved in handwritten character recognition is 99.14%. For testing purposes IDRBT cheque dataset is used comprising cheque leaflets of different banks.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

References

  1. Sabu, A.M., Das, A.N.: A survey on various optical character recognition techniques. In: International Conference on Emerging Devices and Smart Systems, pp. 152–155 (2018)

    Google Scholar 

  2. Sahare, P., Dhok, S.B.: Multilingual character segmentation and recognition schemes for Indian document images. IEEE Access 7, 10603–10607 (2018)

    Article  Google Scholar 

  3. Li, Y., Zhang, J., Gao, P., Jiang, L., Chen, M.: Grab cut image segmentation on image region. In: 3rd International Conference on Image, Vision and Computing, pp. 311–315 (2018)

    Google Scholar 

  4. Lee, S.H., Yang, C.S., Hou, T.W., Yeh, C.H.: An image preprocessing method for fingernail segmentation in microscopy image. In: 2nd International Conference on Signal and Image Processing, pp. 489–493 (2017)

    Google Scholar 

  5. Dorgham, O.M.: Automatic body segmentation from computed tomography image. In: 3rd International Conference on Advanced Technologies, pp. 1–5 (2017)

    Google Scholar 

  6. Brzoza, A., Muszynski, G.: An approach to image segmentation based on shortest paths. In: International Conference on Systems, Signals and Image Processing, pp. 1–5 (2017)

    Google Scholar 

  7. Saddami, K., Afrah, P., Mutiawani, V., Arnia, F.: A new adaptive thresholding technique for binarizing ancient document. In: Indonesian Association for Pattern Recognition International Conference, pp. 57–61 (2017)

    Google Scholar 

  8. Agrawal, N., Kaur, A.: An algorithmic approach for text recognition from printed and typed text images. In: 8th International Conference on Cloud Computing, Data Science & Engineering, pp. 876–879 (2018)

    Google Scholar 

  9. Latha, M.A., Evangeline, N.C., SankaraNarayanan, S.: Colour image segmentation of fundus blood vessels for the detection of hypertensive retinopathy. In: 4th International Conference on Biosignals, Images and Instrumentation, pp. 206–212 (2018)

    Google Scholar 

  10. Vidakis, D.G., Kosmopolous, D.I.: Facilitation of air traffic control via optical character recognition-based aircraft registration number extraction. Inst. Eng. Technol. J. 12, 965–975 (2018)

    Google Scholar 

  11. Yelniz, I.Z., Manmatha, R.: Dependence models for searching text in document images. IEEE Trans. Pattern Anal. Mach. Intell. 41, 49–63 (2018)

    Article  Google Scholar 

  12. Sun, Y., Mao, X., Hong, S., Xu, W., Gui, G.: Template matching-based method for intelligent invoice information identification. IEEE Access 7, 28392–28401 (2019)

    Article  Google Scholar 

  13. Agrawal, P., Kaur, R., Madaan, V., Mukkelli, S.B., Sethi, D.: Moving object detection and recognition using optical flow and eigen face using low resolution video. In: Recent Patents on Computer Science, pp. 1–8. Bentham Science Publisher (2018)

    Google Scholar 

  14. Kaur, G., Agrawal, P.: Optimisation of image fusion using feature matching based on SIFT and RANSAC. Indian J. Sci. Technol. 9, 1–7 (2016)

    Google Scholar 

  15. Monica, Singh, S.K., Agrawal, P., Madaan, V.: Breast cancer diagnosis using digital image segmentation techniques. Indian J. Sci. Technol. 9, 1–5 (2016)

    Google Scholar 

  16. Ben-Musa, A.S., Singh, S.K., Agrawal, P.: Object detection and recognition in cluttered scene using Harris corner detection. In: International Conference on Control, Instrumentation, Communication & Computational Technologies (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Prateek Agrawal .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chaudhary, D., Agrawal, P., Madaan, V. (2019). Bank Cheque Validation Using Image Processing. In: Luhach, A., Jat, D., Hawari, K., Gao, XZ., Lingras, P. (eds) Advanced Informatics for Computing Research. ICAICR 2019. Communications in Computer and Information Science, vol 1075. Springer, Singapore. https://doi.org/10.1007/978-981-15-0108-1_15

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-0108-1_15

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0107-4

  • Online ISBN: 978-981-15-0108-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics