---
title: "Knowledge Utilization in Handwritten Zip Code Recognition"
authors:
  - "Jonathan J. Hull"
  - "Sargur N. Srihari"
doi: ""
url: "https://ijcai.org/proceedings/1987/178"
pdf: "https://ijcai.org/proceedings/1987/0178.pdf"
venue: "Proceedings of the Tenth International Joint Conference on Artificial Intelligence"
year: 1987
pages: "848-849"
track: "Perception"
keywords:
---

# Knowledge Utilization in Handwritten Zip Code Recognition

Jonathan J. Hull, Sargur N. Srihari

*Proceedings of the Tenth International Joint Conference on Artificial Intelligence*, 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.