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
Link To Document