Two Dimension Threshold Image Segmentation Based on Improved Artificial Fish-Swarm Algorithm

DOI

10.2991/cmfe-15.2015.156How to use a DOI?

Keywords

Artificial Fish-swarm Algorithm; 2-D Fisher criterion;threshold;image segmentation

Abstract

To deal with the deficiency of the existing image threshold segmentation algorithm, combining the advantages of Artificial Fish-swarm Algorithm (AFSA), based on the improvement of the AFSA, the thesis proposes a new improved image threshold segmentation algorithm which is the combination of the AFSA and two-dimensional Fisher evaluation function. According to the principle of Fisher pattern recognition, based on two-dimensional histogram, by defining a two-dimensional Fisher criterion functions which is also used as the food concentration function in AFSA, it puts forward a two-dimensional improved image threshold segmentation algorithm. The Experimental results show that the algorithm not only gets the desired segmentation results, but also reduces the time-consuming greatly and thus achieve the fast segmentation goal.

Copyright

© 2015, 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  - Suhua Jiang
AU  - Dongdong Wang
AU  - Chunqiang Liu
PY  - 2015/07
DA  - 2015/07
TI  - Two Dimension Threshold Image Segmentation Based on Improved Artificial Fish-Swarm Algorithm
BT  - Proceedings of the International Conference on Chemical, Material and Food Engineering
PB  - Atlantis Press
SP  - 661
EP  - 664
SN  - 2352-5401
UR  - https://doi.org/10.2991/cmfe-15.2015.156
DO  - 10.2991/cmfe-15.2015.156
ID  - Jiang2015/07
ER  -