• DocumentCode
    188728
  • Title

    Information Quantity Based Automatic Reconstruction of Shredded Chinese Documents

  • Author

    Bo Zhao ; Yu Zhou ; Zhengyu Zhang ; Ying Na ; Tinghuai Ma

  • Author_Institution
    Coll. of Comput. & Software, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
  • fYear
    2014
  • fDate
    10-12 Nov. 2014
  • Firstpage
    1016
  • Lastpage
    1020
  • Abstract
    The reconstruction of shredded documents has a great significance in the fields of forensics, reconstruction of historical documents, and intelligence analysis. The reconstruction of cross-cut shredded Chinese documents is presented in this paper. The Evaluation of Match Degree is divided into two sub-problems, feature and the corresponding scoring function. A new method of the Evaluation of Match Degree which is suitable for shredded Chinese documents is presented. Information Quantity is introduced to measure the reliability of each matching, instead of regarding as the same. A novel and effective algorithm of automatic reconstruction based on Information Quantity is put forward to control the serious propagation of errors caused by the matching of shreds with low Information Quantity. Not only is the propagation of errors controlled effectively, and the error ratio reduced, but also the time complexity decreases greatly. Experiments have proven the high accuracy and superiority of the algorithm proposed in this paper.
  • Keywords
    character recognition; character sets; document image processing; image matching; image reconstruction; text analysis; cross-cut shredded Chinese documents; error ratio; historical documents; information quantity based automatic reconstruction; intelligence analysis; match degree; scoring function; time complexity; Conferences; Gray-scale; IEEE Press; Image reconstruction; Presses; Reliability; Time complexity; Chinese documents; Evaluation of Match Degree; Information Quantity; algorithm of automatic reconstruction; reconstruction of documents; shreds;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference on
  • Conference_Location
    Limassol
  • ISSN
    1082-3409
  • Type

    conf

  • DOI
    10.1109/ICTAI.2014.154
  • Filename
    6984590