Container-code pattern recognition based on attribute grid computing

Liang-Dong Chen, Wei-Ming Zeng, Ni-Zhuan Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

A new container-code pattern recognition algorithm based on attribute grid computing is presented in this paper. The algorithm takes advantage of attribute grid computing, which is a new kind of calculator based on qualitative mapping. In this paper, character feature points are firstly modeled by qualitative criterion attribute grid computing. Then characteristics of each attribute are extracted and the corresponding attribute feature vector is established. Thus, the attribute feature vector can be used to train the model for each container-code character and finally to recognize the characters. By the attribute grid computing, our preliminary experimental results demonstrate an average recognition rate over 97% on hundreds of container-code characters. The results also demonstrate the feasibility of this method.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE International Conference on Granular Computing, GrC 2013
EditorsShuliang Wang, Xingquan Zhu, Tingting He
PublisherIEEE Computer Society
Pages33-37
Number of pages5
ISBN (Print)9781479912810
DOIs
Publication statusPublished - 17 Feb 2014
Externally publishedYes
Event2013 IEEE International Conference on Granular Computing, GrC 2013 - Beijing, China
Duration: 13 Dec 201315 Dec 2013

Conference

Conference2013 IEEE International Conference on Granular Computing, GrC 2013
Country/TerritoryChina
CityBeijing
Period13/12/1315/12/13

Keywords

  • attribute grid computing
  • container-code pattern recognition
  • qualitative criterion
  • qualitative mapping

ASJC Scopus subject areas

  • Software

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