An algorithm based on ODLLTSA and SVM classier for door plate number recognition

Li Ling Ma*, Li Jun Ji, Jun Zheng Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

A new method is proposed, through combining the algorithm of orthogonal discriminant linear local tangent space alignment (ODLLTSA) and the support vector machine (SVM), to improve the accuracy of recognizing door plate numbers. The feature of door plate characters is first extracted by the ODLLTSA and then this extracted feature is used to train the SVM classifier. Finally, the new plate characters are classified by the trained SVM. Using the algorithm, a high recognition rate can be achieved. Experimental results show that this method is effective and robust in the real applications.

Original languageEnglish
Pages (from-to)789-793
Number of pages5
JournalZhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology)
Volume42
Issue numberSUPPL. 1
Publication statusPublished - Sept 2011

Keywords

  • Door plate number recognition
  • Feature extraction
  • ODLLTSA algorithm
  • Support vector machine

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