A Hybrid Method Based on Tissue Membrane Systems and Velocity-Position Model for Image Thresholding

DOI

10.2991/meic-14.2014.135How to use a DOI?

Keywords

image thresholding; membrane computing; tissue membrane systems; total fuzzy entropy

Abstract

This paper proposes an image thresholding segmentation method, which combines tissue membrane systems and velocity-position model. A tissue membrane system is used as its computing framework and an improved velocity-position model is integrated as evolution rules of objects in cells. Due to parallel computing ability and inherent evolution-communication mechanism of the tissue membrane system, the presented hybrid method can effectively and efficiently find the optimal thresholds for three-level thresholding based on total fuzzy entropy. The performance of the presented hybrid method is studied with several evolutionary algorithms. Simulation results show that the presented hybrid method is superior or comparable to the other evolutionary algorithms and can be efficiently used for image thresholding.

Copyright

© 2014, 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  - Xinzhong Yi
AU  - Zulin Zhang
AU  - Hong Peng
PY  - 2014/11
DA  - 2014/11
TI  - A Hybrid Method Based on Tissue Membrane Systems and Velocity-Position Model for Image Thresholding
BT  - Proceedings of the 2014 International Conference on Mechatronics, Electronic, Industrial and Control Engineering
PB  - Atlantis Press
SP  - 602
EP  - 606
SN  - 2352-5401
UR  - https://doi.org/10.2991/meic-14.2014.135
DO  - 10.2991/meic-14.2014.135
ID  - Yi2014/11
ER  -