Segmentation and Recognition of Handwritten Dates

Authors:
M. Morita;R. Sabourin;F. Bortolozzi;C. Y. Suen
Affiliations:
-;-;-;-
Venue:
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Year:
2002

Citing 0
Cited 3

A Recognition and Verification Strategy for Handwritten Word Recognition

ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition

ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
W-TSV: Weighted topological signature vector for lexicon reduction in handwritten Arabic documents

Pattern Recognition

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Abstract

This paper presents an HMM-MLP hybrid system to recognize complex date images written on Brazilian bank cheques. The system first segments implicitly a date image into sub-fields through the recognition process based on an HMM-based approach. Afterwards, the three obligatory date sub-fields are processed by the system (day, month and year). A neural approach has been adopted to work with strings of digits and a Markovian strategy to recognize and verify words. We also introduce the concept of meta-classes of digits, which is used to reduce the lexicon size of the day and year and improve the precision of their segmentation and recognition. Experiments show interesting results on date recognition.