• DocumentCode
    3056764
  • Title

    Automated malaria parasite detection in thin blood films:- A hybrid illumination and color constancy insensitive, morphological approach

  • Author

    Kareem, Saumya ; Kale, I. ; Morling, R.C.S.

  • Author_Institution
    Appl. DSP & VLSI Res. Group, Univ. of Westminster, London, UK
  • fYear
    2012
  • fDate
    2-5 Dec. 2012
  • Firstpage
    240
  • Lastpage
    243
  • Abstract
    This paper illustrates the automated diagnosis of malaria parasite (Plasmodium species) in microscopic images of Giemsa stained thin blood films. The procedure adapts a morphological approach for blood cell identification and uses the image features such as intensity, histogram, relative size and geometry for further analysis. Two methods of object classification have been described for parasite detection; one based on relative size and morphology and the other based on intensity variation. Furthermore, an analytical study on both methods has been performed in order to validate the accuracy of the methods.
  • Keywords
    blood; cellular biophysics; feature extraction; image classification; medical image processing; Giemsa stained thin blood films; automated diagnosis; automated malaria parasite detection; blood cell identification; color constancy; hybrid illumination; image features; intensity variation; microscopic images; morphological approach; object classification; plasmodium species; Accuracy; Blood; Diseases; Films; Image color analysis; Lighting; Microscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems (APCCAS), 2012 IEEE Asia Pacific Conference on
  • Conference_Location
    Kaohsiung
  • Print_ISBN
    978-1-4577-1728-4
  • Type

    conf

  • DOI
    10.1109/APCCAS.2012.6419016
  • Filename
    6419016