Handwritten Bank Check Recognition of Courtesy Amounts

Rafael Palacios, Amar Gupta () and Patrick Wang

No 4461-04, Working papers from Massachusetts Institute of Technology (MIT), Sloan School of Management

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.

Keywords: Handwritten checks; Reading of unconstrained handwritten material; neural network (search for similar items in EconPapers)
Date: 2004-12-10
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