Text-independent writer identification using texture feature

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

Abstract

This paper proposes an efficient method based on texture feature for text-independent writer identification. In order to extract texture feature, we use the modified 2-D Gabor filter, which can decompose the image into sub-bands with different frequencies and orientations. Nearest neighbor classifier based on weighted chi-square distance is utilized in classification. The experiments on a database containing 203 writers of address images demonstrate that the performance of our modified 2-D Gabor filter is better than that of the traditional 2-D Gabor filter and our proposed method achieves promising results.

Original languageEnglish
Title of host publicationAdvances on Digital Television and Wireless Multimedia Communications - 9th International Forum on Digital TV and Wireless Multimedia Communication, IFTC 2012, Proceedings
Pages162-168
Number of pages7
DOIs
StatePublished - 2012
Event9th International Forum on Digital TV and Wireless Multimedia Communication, IFTC 2012 - Shanghai, China
Duration: 9 Nov 201210 Nov 2012

Publication series

NameCommunications in Computer and Information Science
Volume331 CCI
ISSN (Print)1865-0929

Conference

Conference9th International Forum on Digital TV and Wireless Multimedia Communication, IFTC 2012
Country/TerritoryChina
CityShanghai
Period9/11/1210/11/12

Keywords

  • modified 2-D Gabor filter
  • weighted chisquare distance
  • writer identification

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