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ASME Press Select Proceedings

International Conference on Information Technology and Computer Science, 3rd (ITCS 2011)

Editor
V. E. Muhin
V. E. Muhin
National Technical University of Ukraine
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W. B. Hu
W. B. Hu
Wuhan University
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ISBN:
9780791859742
No. of Pages:
656
Publisher:
ASME Press
Publication date:
2011

Feature extraction and selection is an important procedure in cell image quantitative analysis and automatic recognition. In this paper, four kinds of features, morphological features, chromatic features, optical density features and texture features are extracted over cell body area, or nucleus area or cytoplasm area and 87 features in all are extracted. Considering the correlation and redundancy of selected features, we propose genetic algorithm using expression of larger between-class scatter and smaller within-class scatter as fitness function to evolve the optimal individual, and 35 features are selected as optimal features to do further cell classification.

Abstract
Keywords
Introduction
Feature Extraction
Feature Selection
Simulation Experiment
Conclusions
Reference
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