Knowledge Utilization in Handwritten Zip Code Recognition

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 subfixes 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 ZlP+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.

Cite

Text

Hull and Srihari. "Knowledge Utilization in Handwritten Zip Code Recognition." International Joint Conference on Artificial Intelligence, 1987.

Markdown

[Hull and Srihari. "Knowledge Utilization in Handwritten Zip Code Recognition." International Joint Conference on Artificial Intelligence, 1987.](https://mlanthology.org/ijcai/1987/hull1987ijcai-knowledge/)

BibTeX

@inproceedings{hull1987ijcai-knowledge,
  title     = {{Knowledge Utilization in Handwritten Zip Code Recognition}},
  author    = {Hull, Jonathan J. and Srihari, Sargur N.},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {1987},
  pages     = {848-850},
  url       = {https://mlanthology.org/ijcai/1987/hull1987ijcai-knowledge/}
}