• DocumentCode
    604558
  • Title

    Research of license plate character features extraction and recognition

  • Author

    Liu Yongchun ; Yang Jing

  • Author_Institution
    Sch. of Autom. & Electron. Inf., Sichuan Univ. of Sci. & Eng., Zigong, China
  • fYear
    2012
  • fDate
    29-31 Dec. 2012
  • Firstpage
    2154
  • Lastpage
    2157
  • Abstract
    A license plate character cascading recognition algorithm based on structure and gray pixel features is presented in this paper. First, it extracts character\´s stroke features, inflection point features, contour accumulation features from the preprocessed license plate characters; and then, extracts the pixel features from the character\´s gray images with PCA algorithm; finally, uses support vector machine (SVM) to respectively construct structure feature classifiers and gray pixel feature classifiers and recognize characters, at the same time, takes the results with higher confidence level as the first classification results from the both classifications. If the results are "8", "B" and the other easily confused characters, then reclassifies characters using the gray pixel classifier and yields the final results; if they are "0","D"and the other characters with similar structure features, and then uses the structure classifiers to classify again.
  • Keywords
    character recognition; feature extraction; image classification; principal component analysis; support vector machines; PCA algorithm; SVM; character stroke feature extraction; contour accumulation features; gray pixel feature classifier; inflection point features; license plate character cascading recognition algorithm; license plate character feature extraction; principal component analysis; structure feature classifier; support vector machine; PCA; SVM; feature extraction; license plate recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-4673-2963-7
  • Type

    conf

  • DOI
    10.1109/ICCSNT.2012.6526344
  • Filename
    6526344