• DocumentCode
    2148191
  • Title

    Adaptive Zoning Features for Character and Word Recognition

  • Author

    Gatos, B. ; Kesidis, A.L. ; Papandreou, A.

  • Author_Institution
    Comput. Intell. Lab., Nat. Center for Sci. Res. Demokritos, Athens, Greece
  • fYear
    2011
  • fDate
    18-21 Sept. 2011
  • Firstpage
    1160
  • Lastpage
    1164
  • Abstract
    Zoning features are of the most popular and efficient statistical features that provide high speed and low complexity for character and word recognition. They are calculated by the density of pixels or pattern characteristics in several zones we divide the pattern frame. In this paper, we introduce the idea of adaptive zoning features that are extracted after adjusting the position of every zone based on local pattern information. This adjustment is performed by moving every zone towards the pattern body. This process is based on the maximization of the local pixel density around each zone. We have extensively tested our approach for character and word recognition as well as for using the pixel density or pattern characteristics in every zone. For all cases, we have recorded a significant improvement when the zoning features are used in the proposed adaptive way.
  • Keywords
    character recognition; feature extraction; image classification; optimisation; statistical analysis; word processing; adaptive zoning features; character recognition; feature extraction; local pixel density; maximization; pattern characteristics; pattern frame; statistical features; word recognition; Accuracy; Character recognition; Data mining; Feature extraction; Handwriting recognition; Skeleton; Character Recognition; Word Recognition; Zoning Features;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Document Analysis and Recognition (ICDAR), 2011 International Conference on
  • Conference_Location
    Beijing
  • ISSN
    1520-5363
  • Print_ISBN
    978-1-4577-1350-7
  • Electronic_ISBN
    1520-5363
  • Type

    conf

  • DOI
    10.1109/ICDAR.2011.234
  • Filename
    6065492