Fast title extraction method for business documents

Yutaka Katsuyama*, Satoshi Naoi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Conventional electronic document filing systems are inconvenient because the user must specify the keywords in each document for later searches. To solve this problem, automatic keyword extraction methods using natural language processing and character recognition have been developed. However, these methods are slow, especially for japanese documents. To develop a practical electronic document filing system, we focused on the extraction of keyword areas from a document by image processing. Our fast title extraction method can automatically extract titles as keywords from business documents. All character strings are evaluated for similarity by rating points associated with title similarity. We classified these points as four items: character sitting size, position of character strings, relative position among character strings, and string attribution. Finally, the character string that has the highest rating is selected as the title area. The character recognition process is carried out on the selected area. It is fast because this process must recognize a small number of patterns in the restricted area only, and not throughout the entire document. The mean performance of this method is an accuracy of about 91 percent and a 1.8 sec. processing time for an examination of 100 Japanese business documents.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSociety of Photo-Optical Instrumentation Engineers
Pages192-201
Number of pages10
ISBN (Print)0819424382
Publication statusPublished - 1997
Externally publishedYes
EventDocument Recognition IV - San Jose, CA, USA
Duration: 1997 Feb 121997 Feb 13

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume3027
ISSN (Print)0277-786X

Conference

ConferenceDocument Recognition IV
CitySan Jose, CA, USA
Period97/2/1297/2/13

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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