Abstract
There are several image segmentation algorithms; each one has its advantages and its limits. In this work, we aim to use the advantages of two algorithms, in a massive multi-agents environment. We use the FCM (Fuzzy C-Mean) algorithm, to manage uncertainty and imprecision and the Region Growing algorithm, to act locally on the image. The massive multi-agents paradigm is then introduced into the region growing process in order to improve the segmentation quality. However in some cases some defaults appear in the segmented image, we propose then the use of a double predicate for the Region Growing algorithm, through a massive cooperative process, in order to improve the quality of the segmented image. Massiveness of the system allows for a better quality analysis.
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© 2005 Springer-Verlag Berlin Heidelberg
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Haroun, R., Boumghar, F., Hassas, S., Hamami, L. (2005). A Massive Multi-agent System for Brain MRI Segmentation. In: Ishida, T., Gasser, L., Nakashima, H. (eds) Massively Multi-Agent Systems I. MMAS 2004. Lecture Notes in Computer Science(), vol 3446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11512073_13
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DOI: https://doi.org/10.1007/11512073_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26974-8
Online ISBN: 978-3-540-31889-7
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