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Handwritten Bank Check Recognition of Courtesy Amounts

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Author Info

  • Palacios, Rafael
  • Gupta, Amar
  • Wang, Patrick

Abstract

In spite of rapid evolution of electronic techniques, a number of large-scale applications continue to rely on the use of paper as the dominant medium. This is especially true for processing of bank checks. This paper examines the issue of reading the numerical amount field. In the case of checks, the segmentation of unconstrained strings into individual digits is a challenging task because of connected and overlapping digits, broken digits, and digits that are physically connected to pieces of strokes from neighboring digits. The proposed architecture involves four stages: segmentation of the string into individual digits, normalization, recognition of each character using a neural network classifier, and syntactic verification. Overall, this paper highlights the importance of employing a hybrid architecture that incorporates multiple approaches to provide high recognition rates.

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File URL: http://hdl.handle.net/1721.1/7386
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Bibliographic Info

Paper provided by Massachusetts Institute of Technology (MIT), Sloan School of Management in its series Working papers with number 4461-04.

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Date of creation: 10 Dec 2004
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Handle: RePEc:mit:sloanp:7386

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Postal: MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT), SLOAN SCHOOL OF MANAGEMENT, 50 MEMORIAL DRIVE CAMBRIDGE MASSACHUSETTS 02142 USA
Phone: 617-253-2659
Web page: http://mitsloan.mit.edu/
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Postal: MASSACHUSETTS INSTITUTE OF TECHNOLOGY (MIT), SLOAN SCHOOL OF MANAGEMENT, 50 MEMORIAL DRIVE CAMBRIDGE MASSACHUSETTS 02142 USA

Related research

Keywords: Handwritten checks; Reading of unconstrained handwritten material; neural network;

This paper has been announced in the following NEP Reports:

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