Automatic Segmentation and Recognition of Bank Cheque Fields

Madasu, Vamsi K. and Lovell, Brian C. (2005). Automatic Segmentation and Recognition of Bank Cheque Fields. In: B. C. Lovell, A. J. Maeder, T. Caelli and S. Ourselin, Proceedings of the Digital Imaging Computing: Techniques and Applications (DICTA 2005). Digital Image Computing: Techniques and Applications (DICTA 20005), Cairns, (223-228). 6-8 December, 2005.

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Author Madasu, Vamsi K.
Lovell, Brian C.
Title of paper Automatic Segmentation and Recognition of Bank Cheque Fields
Conference name Digital Image Computing: Techniques and Applications (DICTA 20005)
Conference location Cairns
Conference dates 6-8 December, 2005
Proceedings title Proceedings of the Digital Imaging Computing: Techniques and Applications (DICTA 2005)
Place of Publication Los Altimos, CA
Publisher IEEE CS Press
Publication Year 2005
Sub-type Fully published paper
ISBN 0-7695-2467-2
Editor B. C. Lovell
A. J. Maeder
T. Caelli
S. Ourselin
Volume 1
Issue 1
Start page 223
End page 228
Total pages 6
Language eng
Abstract/Summary This paper describes a novel method for automatically segmenting and recognizing the various information fields present on a bank cheque. The uniqueness of our approach lies in the fact that it doesn't necessitate any prior information and requires minimum human intervention. The extraction of segmented fields is accomplished by means of a connectivity based approach. For the recognition part, we have proposed four innovative features, namely; entropy, energy, aspect ratio and average fuzzy membership values. Though no particular feature is pertinent in itself but a combination of these is used for differentiating between the fields. Finally, a fuzzy neural network is trained to identify the desired fields. The system performance is quite promising on a large dataset of real and synthetic cheque images.
Subjects 280208 Computer Vision
280207 Pattern Recognition
Keyword iris-research
bank cheques
fuzzy neural networks
information extraction
References [1] J. Blodgett, Beyond cheque image statements: A new strategy for the 1990s, Advance Imaging, Vol. 9, pp. 73-75, 1994. [2] T.G. Holland, Cheques and Balances, Security Management, Vol. 43, pp. 76-82, 1999. [3] C.Y. Suen, Q. Xu and L. Lam, Automatic recognition of handwritten data on cheques - Fact or Fiction?" Pattern Recognition Letters, Vol.20, pp. 1287-1295, 1999. [4] R. Fan, L. Lam, and C.Y. Suen, Processing of date information on cheques, Progress in Handwriting Recognition, World Scientific, pp.473-479, 1997. [5] S. Kelland and S. Wesolkowski, A comparison of Research and Production Architectures for Cheque Reading Systems, Proceedings of the 5th International Conference on Document Analysis and Recognition, pp. 99-102, 1999. [6] J-H Chiang, Choquet fuzzy integral based hierarchical networks for decision analysis, IEEE Transactions on Fuzzy Systems, Vol.7, no.1, 1999 pp. 63-71. [7] B.B. Choudhari and N. Sarkar, Texture segmentation using fractal dimension, IEEE Transactions on PAMI, Vol.17, No.1, 1995, pp. 72-77. [8] V.K. Madasu, M.H.M. Yusof, M. Hanmandlu and K. Kubik, Automatic extraction of signatures from bank cheques and other documents, Proceedings of DICTA, vol. 2, pp. 591-600, 2003. [9] K. Han and I. Sethi, An off-line cursive handwritten word recognition system and its application to legal amount interpretation, Automatic Bankcheque Processing, World Scientific, pp. 295-308, 1997. [10] K. Liu, C.Y. Suen, and C. Nadal, Automatic extraction of items from cheque images for payment recognition, Proceedings of the Intl. Conference on Pattern Recognition, pp. 798 - 802, 1996. [11] K. Liu, C.Y. Suen, M. Cheriet, J.N. Said, C. Nadal, and Y.Y. Tang, Automatic Extraction of Baselines and Data from Cheque Images, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 11, pp. 675-697, 1997.
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

 
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Created: Tue, 14 Feb 2006, 10:00:00 EST by Brian C. Lovell on behalf of Social Sciences and Humanities Library Service