Genetic algorithms and multifractal segmentation of cervical cell images

dc.contributor.authorLassouaoui, Nadia
dc.contributor.authorHamami, Latifa
dc.description.abstractThis paper deals with the segmentation problem of cervical cell images. Knowing that the malignity criteria appear on the morphology of the core and the cytoplasm of each cell, then, the goal of this segmentation is to separate each cell on its component, that permits to analyze separately their morphology (size and shape) in the recognition step, for deducing decision about the malignity of each cell. For that, we use a multifractal algorithm based on the computation of the singularity exponent on each point of the image. For increasing the quality of the segmentation, we propose to add an optimization step based on genetic algorithms. The proposed processing has been tested on several images. Herein, we present some results obtained by two cervical cell images.fr_FR
dc.relation.ispartofISSPA'03 : Signal Processing and Its Applications, 2003. Proceedings, Seventh International Symposium onfr_FR
dc.relation.placeParis, Francefr_FR
dc.rights.holderIEEE Computer Societyfr_FR
dc.subjectApplication softwarefr_FR
dc.subjectBiological cellsfr_FR
dc.subjectComputer visionfr_FR
dc.subjectGenetic algorithmsfr_FR
dc.subjectGenetic mutationsfr_FR
dc.subjectImage segmentationfr_FR
dc.titleGenetic algorithms and multifractal segmentation of cervical cell imagesfr_FR
dc.typeConference paper