Knowledge Utilization in Handwritten Zip Code Recognition
Proceedings of the Tenth International Joint Conference on Artificial Intelligence. Perception. Pages 848-849.
Abstract
The process of recognizing the postal codes or zip codes in a handwritten address can be aided by many sources of external knowledge. City and state names are obvious examples that can be used in conjunction with a city-state-zip directory to provide evidence about digits in a zip code. This paper describes an extension of this methodology that uses knowledge about legal street names and suffixes to constrain the digits in a zip code. The technique does not require complete recognition of all characters in words. Rather, a feature description of words is used to index a set of possible zip codes. Some preliminary experiments with the ZIP+4 database are discussed. It is shown that even a relatively simple description of two words in the street line of an address can significantly reduce the number of zip codes that could appear on a piece of mail.
@inproceedings{ijcai1987p178,
title = {Knowledge Utilization in Handwritten Zip Code Recognition},
author = {Hull, Jonathan J. and Srihari, Sargur N.},
booktitle = {Proceedings of the Tenth International Joint Conference on
Artificial Intelligence, {IJCAI-87}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {John McDermott},
pages = {848--849},
year = {1987},
note = {Perception},
url = {https://ijcai.org/proceedings/1987/178},
}
TY - CPAPER TI - Knowledge Utilization in Handwritten Zip Code Recognition AU - Hull, Jonathan J. AU - Srihari, Sargur N. T2 - Proceedings of the Tenth International Joint Conference on Artificial Intelligence, IJCAI-87 PB - International Joint Conferences on Artificial Intelligence PY - 1987 SP - 848 EP - 849 UR - https://ijcai.org/proceedings/1987/178 ER -Copied
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