C. Meurie, O. Lezoray, C. Charrier, and A. Elmoataz
Classiﬁer combination, segmentation, pixel classiﬁcation, colour, microscopy
The combination of classifiers has been proposed as a method
allowing to improve the quality of recognition systems as compared
to a single classifier. This paper describes a segmentation scheme
based on a combination of pixel classifications. The aim of this
article is to show the influence of the neighbourhood information
and of the number of classiﬁers used in several combination processes. In the first part, we detail the ground of our study for
a microscopic application. Then, we name the different steps of
the new segmentation scheme. In the third and fourth part, we
detail the different rules that can be used to combine classifiers and
the classifications results obtained on colour microscopic images.
Finally, we draw a conclusion on the improvement of the quality of
the segmentation at the end of treatment.