Fast and Global Minimization Convex Multiphase Active Contours

DOI

10.2991/icsnce-16.2016.92How to use a DOI?

Keywords

Image segmentation; Active contour model; Multiphase; Global Minimization

Abstract

Biomedical images usually have multiple regions of interest, which lead to the study of multi object segmentation in this area. Multiphase level set active contour model using a gradient descent method to minimize energy non convex, so not only will be the local minimum, but also lead to erroneous segmentation, the fast algorithm can not be carried out, can not be solved quickly. Aiming at the above problems,we propose a multi object image segmentation algorithm of global convex coupling. First, in order to avoid the segmented regions overlap and vacuum, we put two-phase level set Chan Vese model was extended to four phase, and the introduction of edge stopping function improved regularization process, and then based on this model of convex optimization, to obtain the global optimal solution, finally, using dual minimization method for the fast calculation. Experimental results show that the proposed model can not only obtain the global optimal solution, but also greatly improve the efficiency and accuracy of the segmentation.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lifen Zhou
AU  - Shunji Zhang
PY  - 2016/07
DA  - 2016/07
TI  - Fast and Global Minimization Convex Multiphase Active Contours
BT  - Proceedings of the 2016 International Conference on Sensor Network and Computer Engineering
PB  - Atlantis Press
SP  - 471
EP  - 476
SN  - 2352-5401
UR  - https://doi.org/10.2991/icsnce-16.2016.92
DO  - 10.2991/icsnce-16.2016.92
ID  - Zhou2016/07
ER  -