Fusion of SVM-Based Microscopic Color Images Through Colorimetric Transformation

Author

Charrier, Christophe ; Lebrun, Gilles ; Lezoray, Olivier

Author_Institution

Vision & Image Anal. Group, Caen Basse-Normandie Univ.

Volume

2

fYear

2006

fDate

14-19 May 2006

Abstract

A tool for diagnosis assistance by automatic segmentation of microscopic cellular images is introduced. This method is based on an automatic segmentation technique combining (with the Dempster-Shafer rule) the results obtained by support vector machines (SVM) applied within different color spaces. This combination is performed by integrating uncertainties and redundancies for each color space. Those uncertainties are computed as a posteriori probabilities according to the SVM obtained results. An improvement of the final segmentation quality is performed by taking into account the inconsistencies of several pixel classifications

Keywords

cellular biophysics; image classification; image colour analysis; image resolution; image segmentation; medical image processing; microscopy; support vector machines; Dempster-Shafer rule; SVM-based microscopic color images; automatic segmentation; colorimetric transformation; microscopic cellular images; pixel classifications; posteriori probabilities; support vector machines; Image color analysis; Image segmentation; Kernel; Microscopy; Risk management; Statistical learning; Support vector machine classification; Support vector machines; Training data; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on

Conference_Location

Toulouse

ISSN

1520-6149

Print_ISBN

1-4244-0469-X

Type

conf

DOI

10.1109/ICASSP.2006.1660542

Filename

1660542