Stammdaten

Titel: Bank Cheque Validation Using Image Processing
Untertitel:
Kurzfassung:

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.

Schlagworte: Optional Character Recognition (OCR), Artificial Neural Network (ANN), Convolutional Neural Network (CNN), Reserve Bank of India (RBI), Morphological operations
Publikationstyp: Beitrag in Proceedings (Autorenschaft)
Erscheinungsdatum: 17.09.2019 (Online)
Erschienen in: Proceedings of the 3rd International Conference On Advanced Informatics For Computing Research
Proceedings of the 3rd International Conference On Advanced Informatics For Computing Research
zur Publikation
 ( Springer Singapore; A. Luhach, D. Jat, K. Hawari, X. Gao, P. Lingras )
Titel der Serie: Communications in Computer and Information Science
Bandnummer: -
Erstveröffentlichung: Ja
Version: -
Seite: S. 148 - 159

Versionen

Keine Version vorhanden
Erscheinungsdatum: 17.09.2019
ISBN (e-book):
  • 978-981-15-0107-4
  • 978-981-15-0108-1
eISSN: -
DOI: http://dx.doi.org/10.1007/978-981-15-0108-1_15
Homepage: https://link.springer.com/chapter/10.1007/978-981-15-0108-1_15
Open Access
  • Online verfügbar (nicht Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Österreich
   martina.steinbacher@aau.at
http://itec.aau.at/
zur Organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 202022 - Informationstechnik
Forschungscluster Kein Forschungscluster ausgewählt
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: I)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Distributed Multimedia Systems

Kooperationen

Organisation Adresse
Lovely Professional University
Jalandhar - Delhi G.T. Road
Phagwara, Punjab
Indien
https://www.lpu.in/
Jalandhar - Delhi G.T. Road
IN  Phagwara, Punjab

Beiträge der Publikation

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