Writer Identification Using Differential Chain Codes and Grid Features

Zhimin Huang, Dongli Wang*, Yue Lu

*Corresponding author for this work

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

1 Scopus citations

Abstract

This paper proposes an efficient method for writer identification in handwritten documents. The method operates at two stages: rough matching and fine matching. At the first stage, the histograms of the first and second order differential chain codes are extracted and used in rough matching. At the second stage, the histograms of the positions of connected edge pixel pairs in a floating grid are recorded and applied to the fine matching. At each stage, two writings are compared by computing the distances between their respective histograms. The experiments are implemented on two common data sets: HIT-MW and IAM, which contain samples of Chinese and English handwritten texts. The experimental results show that the proposed methods achieve promising results on writer identification.

Original languageEnglish
Title of host publicationFoundations of Intelligent Systems - Proceedings of the 8th InternationalConference on Intelligent Systems and Knowledge Engineering, ISKE 2013
PublisherSpringer Verlag
Pages647-656
Number of pages10
ISBN (Print)9783642549236
DOIs
StatePublished - 2014
Event8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013 - Shenzhen, China
Duration: 20 Nov 201323 Nov 2013

Publication series

NameAdvances in Intelligent Systems and Computing
Volume277
ISSN (Print)2194-5357

Conference

Conference8th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2013
Country/TerritoryChina
CityShenzhen
Period20/11/1323/11/13

Keywords

  • Fine matching
  • Global level
  • Local level
  • Rough matching
  • Writer identification

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