An HMM-Based Legal Amount Field OCR System for Checks (1995)
| Venue: | IEEE International Conference on Systems, Man and Cybernetics, Vancouver BC |
| Citations: | 10 - 5 self |
BibTeX
@INPROCEEDINGS{Kornai95anhmm-based,
author = {Andras Kornai and K. M. Mohiuddin and Scott D. Connell},
title = {An HMM-Based Legal Amount Field OCR System for Checks},
booktitle = {IEEE International Conference on Systems, Man and Cybernetics, Vancouver BC},
year = {1995},
pages = {2800--2805}
}
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Abstract
The system described in this paper applies Hidden Markov technology to the task of recognizing the handwritten legal amount on personal checks. We argue that the most significant source of error in handwriting recognition is the segmentation process. In traditional handwriting OCR systems, recognition is performed at the character level, using the output of an independent segmentation step. Using a fixed stepsize series of vertical slices from the image, the HMM system described in this paper avoids taking segmentation decisions early in the recognition process. 0 Introduction The current generation of Optical Character Recognition (OCR) systems can be characterized as a pipeline composed of Preprocessing, Segmentation, Classification, and Identification stages. None of these stages are immune to error. Preprocessing may fail to remove existing noise, it may remove portions of the image or add noise by some other mechanism. Segmentation may fail to establish a boundary where there sh...
