• DocumentCode
    2609796
  • Title

    An Off-line Chinese Writer Retrieval System Based on Text-sensitive Writer Identification

  • Author

    Li, Xin ; Wang, Xianliang ; Ding, Xiaoqing

  • Author_Institution
    Dept. of Electron. Eng., Tsinghua Univ., Beijing
  • Volume
    4
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    517
  • Lastpage
    520
  • Abstract
    In this paper an off-line Chinese writer retrieval system based on text-sensitive writer identification is practised. OCR technique is used to mark the handwritten script content. The used text-sensitive writer identification algorithm extracts directional element features (DEFs), reduces the dimensions using PCA and LDA, and adopts the simple Euclidean classifier. By introducing negative samples, the similarity measure is more comprehensive. However the writer identification algorithm is text-sensitive, a novel method for retrieving in an amount of writers who has different handwriting script content is proposed in this paper, by combining and sorting the confidence results of writing identification. An experiment, which is carried out in a handwriting script database, demonstrates the effectiveness of the proposed method
  • Keywords
    feature extraction; image retrieval; natural languages; optical character recognition; principal component analysis; text analysis; Euclidean classifier; LDA; OCR technique; PCA; directional element features; feature extraction; handwriting script database; handwritten script content; offline Chinese writer retrieval system; text-sensitive writer identification; Character recognition; Content based retrieval; Feature extraction; Image recognition; Intelligent systems; Laboratories; Linear discriminant analysis; Optical character recognition software; Principal component analysis; Writing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.262
  • Filename
    1699892