Title :
An HMM-based legal amount field OCR system for checks
Author :
Kornai, András ; Mohiuddin, K.M. ; Connell, Scott D.
Author_Institution :
IBM Almaden Res. Center, San Jose, CA, USA
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
Keywords :
bank data processing; feature extraction; hidden Markov models; image segmentation; learning systems; optical character recognition; OCR system; dimension reduction; feature extraction; handwritten character recognition; handwritten legal amount; hidden Markov model; optical character recognition; personal checks; segmentation; Computer errors; Computer science; Hidden Markov models; Image segmentation; Law; Legal factors; Optical character recognition software; Optical noise; Paper technology; Pipelines;
Conference_Titel :
Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-2559-1
DOI :
10.1109/ICSMC.1995.538206