Image Segmentation Analysis based on Maximum Entropy Algorithm

DOI

10.2991/isrme-15.2015.271How to use a DOI?

Keywords

image; segmentation; analysis; algorithm; maximum entropy;

Abstract

This paper introduces the definition of maximum entropy,the principle of one-dimensional and 2-D maximum entropy. This paper solves the image segmentation problem by using the maximum entropy algorithm.The image gray value is divided into two regions of the background and the object.The key problem associated with this method is to find the optimal parameter extracting objects from background, the proposed method is used to segment image and ideal segmentation results can be obtained with less computation cost.Experimental simulation shows that the algorithm has a higher accuracy while preserving the edge infomation,and maximum entropy has been proven to be an efficient method for image segmentation.

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  - Rong Chen
PY  - 2015/04
DA  - 2015/04
TI  - Image Segmentation Analysis based on Maximum Entropy Algorithm
BT  - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering
PB  - Atlantis Press
SP  - 1360
EP  - 1364
SN  - 1951-6851
UR  - https://doi.org/10.2991/isrme-15.2015.271
DO  - 10.2991/isrme-15.2015.271
ID  - Chen2015/04
ER  -