{"type":"ScholarlyArticle","title":"Knowledge Utilization in Handwritten Zip Code Recognition","authors":[{"name":"Jonathan J. Hull","slug":"jonathan-j-hull","given":"Jonathan J.","family":"Hull","affiliation":""},{"name":"Sargur N. Srihari","slug":"sargur-n-srihari","given":"Sargur N.","family":"Srihari","affiliation":""}],"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.","doi":null,"url":"https://ijcai.org/proceedings/1987/178","pdf":"https://ijcai.org/proceedings/1987/0178.pdf","markdown":"https://ijcai.org/proceedings/1987/178.md","bibtex":"https://ijcai.org/proceedings/1987/bibtex/178","volume":{"slug":"1987","title":"Proceedings of the Tenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1987","url":"https://ijcai.org/proceedings/1987/","year":1987,"location":"Milan, Italy","dates":"","editors":"John McDermott","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Perception","track":"Perception","number":178,"pages":{"first":848,"last":849},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}