2,997 research outputs found
Handwritten Bank Check Recognition of Courtesy Amounts
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
A Knowledge based segmentation algorithm for enhanced recognition of handwritten courtesy amounts
"March 1994."Includes bibliographical references (p. [23]-[24]).Supported by the Productivity From Information Technology (PROFIT) Research Initiative at MIT.Karim Hussein ... [et al.
Feedback Based Architecture for Reading Check Courtesy Amounts
In recent years, a number of large-scale applications continue to rely heavily on the use of paper as the
dominant medium, either on intra-organization basis or on inter-organization basis, including paper
intensive applications in the check processing application. In many countries, the value of each check is
read by human eyes before the check is physically transported, in stages, from the point it was presented
to the location of the branch of the bank which issued the blank check to the concerned account holder.
Such process of manual reading of each check involves significant time and cost. In this research, a new
approach is introduced to read the numerical amount field on the check; also known as the courtesy
amount field. In the case of check processing, the segmentation of unconstrained strings into individual
digits is a challenging task because one needs to accommodate special cases involving: connected or
overlapping digits, broken digits, and digits physically connected to a piece of stroke that belongs to a
neighboring digit. The system described in this paper involves three stages: segmentation, normalization,
and the recognition of each character using a neural network classifier, with results better than many other
methods in the literaratu
An Integrated architecture for recognition of totally unconstrained handwritten numerals
Reprint. Reprinted from the International journal of pattern recognition and artificial intelligence. Vol. 7, no. 4 (1993) "January 1993."Includes bibliographical references (p. 127-128).Supported by the Productivity From Information Technology (PROFIT) Research Initiative at MIT.Amar Gupta ... [et al.
Integration of traditional imaging, expert systems, and neural network techniques for enhanced recognition of handwritten information
Includes bibliographical references (p. 33-37).Research supported by the I.F.S.R.C. at M.I.T.Amar Gupta, John Riordan, Evelyn Roman
Decision Fusion and Contextual Information for Arabic Words Recognition for Computing and Informatics
The study of multiple classifier systems has become recently an area of intensive research in pattern recognition. Also in handwriting recognition, systems combining several classifiers have been investigated. An approach for recognizing the legal amount for handwritten Arabic bank check is described in this article. The solution uses multiple information sources to recognize words. The recognition step is preformed with a parallel combination of three kinds of classifiers using holistic word structural features. The classification stage results are first normalized, and the sum combination is performed as a decision fusion scheme, after which a syntactic analyzer makes final decision on the candidate words. Using this approach, the obtained results are very interesting and promising
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