• DocumentCode
    2350039
  • Title

    Bayesian classification of eigencells

  • Author

    Sanei, S. ; Lee, T.K.

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Singapore Polytech., Singapore
  • Volume
    2
  • fYear
    2002
  • fDate
    2002
  • Abstract
    A new method for identification of blood cells based on the Bayesian classification of eigencells is introduced. The work by M. Turk and A. Pentland on face recognition (see J. Cognitive Neuroscience, vol.3, no.1, p.71-86, 1991) has been modified and used for cell recognition. Their method lacks a suitable means of eigenvector selection. Also, only monochrome images have been considered and the method is not tolerant enough to geometrical changes. We extend the idea to colour patterns. A fast method in size and rotation adjustment preprocesses the images, the eigencells are selected based on minimisation of similarities among various sets and, finally, a classifier identifies cell types by looking at three-fold intensity-colour information. This overcomes many problems in cell classification where either certain cells are recognised or some constraints such as geometrical variations are involved.
  • Keywords
    Bayes methods; biology computing; blood; cellular biophysics; eigenvalues and eigenfunctions; image classification; image colour analysis; medical image processing; object recognition; Bayesian classification; blood cell identification; bone marrow cells; cell classification; cell recognition; colour patterns; disease diagnosis; eigencells; eigenvector selection; molecular biology; three-fold intensity-colour information; Bayesian methods; Biology computing; Blood; Bone diseases; Cells (biology); Face recognition; Histograms; Mechanical systems; Minimization methods; Morphology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing. 2002. Proceedings. 2002 International Conference on
  • ISSN
    1522-4880
  • Print_ISBN
    0-7803-7622-6
  • Type

    conf

  • DOI
    10.1109/ICIP.2002.1040104
  • Filename
    1040104