A hybrid recognition method for document images

Yudong Zhang*, Lenan Wu, Shuihua Wang

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

5 Citations (Scopus)

Abstract

In order to improve the performance of document image recognition, a GLCM-based classifier is firstly proposed and the shortcomings are analyzed. Then, new features based on Rectangular frame histogram (RFH) are presented and added to the feature set. The hybrid classifier performs better than GLCM-based classifier in terms of classification and false-alarm ratio.

Original languageEnglish
Title of host publicationProceedings of the 12th IASTED International Conference on Intelligent Systems and Control, ISC 2009
Pages62-66
Number of pages5
Publication statusPublished - 2009
Externally publishedYes
Event12th IASTED International Conference on Intelligent Systems and Control, ISC 2009 - Cambridge, MA, United States
Duration: 2 Nov 20094 Nov 2009

Publication series

NameProceedings of the IASTED International Conference on Intelligent Systems and Control
ISSN (Print)1025-8973

Conference

Conference12th IASTED International Conference on Intelligent Systems and Control, ISC 2009
Country/TerritoryUnited States
CityCambridge, MA
Period2/11/094/11/09

Keywords

  • Document image
  • Gray-level co-occurrence matrix

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