• DocumentCode
    2132667
  • Title

    Color image segmentation using false colors and its applications to geo-images treatment: alphanumeric character recognition

  • Author

    Levachkine, Serguei ; Velázquez, Aurelio ; Alexandrov, Victor

  • Author_Institution
    Lab. of Digital Image Process., Inst. Politecnico Nacional, Mexico City, Mexico
  • Volume
    5
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    2212
  • Abstract
    In this work an approach is proposed to segment the alphanumeric characters that present in a cartographic color map, using the model-of color RGB. Corresponding raster image is obtained by means of scanning, following to the strategies proposed in S. Levachkine et al. (2000). Our approach does not require a preprocessing of the images, because they only maintain the pixels that really belong to the characters we wish to segment, eliminating all those pixels that are not of interest, produced by a noise or obtained due to erroneous selection of scan parameters (for example, scan resolution), etc. The following identification of the alphanumeric characters supports by a set of neural network and the dictionaries with the character names related to the map or particular application that has previously been prepared
  • Keywords
    cartography; character recognition; geophysical techniques; geophysics computing; image colour analysis; image segmentation; pattern recognition; cartography; color map; colour graphics; colur map; computer graphics; false color; false colour; geophysical measurement technique; geophysics computing; image segmentation; letter; number; pattern recognition; raster image; scanned map; Application software; Automation; Character recognition; Color; Digital images; Geographic Information Systems; Image segmentation; Informatics; Laboratories; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International
  • Conference_Location
    Sydney, NSW
  • Print_ISBN
    0-7803-7031-7
  • Type

    conf

  • DOI
    10.1109/IGARSS.2001.977952
  • Filename
    977952