Evolutionary Fuzzy Rule Construction for Iterative Object Segmentation

Junji Otsuka, Tomoharu Nagao

2014

Abstract

This paper presents Cellular Fuzzy Oriented Classifier Evolution (CFORCE), a generic method for constructing fuzzy rules to divide an image into two segments: object and background. In CFORCE, a pair of fuzzy classification rule sets for object and background is defined as a processing unit, and the identical units are allocated on each pixel over an input image. Each unit computes matching degree of each pixel with object and background class iteratively with considering the matching degree of neighbor units. The algorithm has mainly two features: 1) designing the fuzzy rules using Fuzzy Oriented Classifier Evolution (FORCE) which develops fuzzy rules represented as directed graphs flexibly and automatically by Genetic Algorithm, and 2) performing iterative segmentation with considering spatial relationship between pixels besides local features. In natural image segmentation, many pixels are overlapped between different clusters. Considering the spatial relationship is important to classify the overlapped pixels correctly. We applied CFORCE to three different object segmentation, and showed that CFORCE extracted object regions successfully.

Paper Citation

in Harvard Style

Otsuka J. and Nagao T. (2014). Evolutionary Fuzzy Rule Construction for Iterative Object Segmentation . In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-015-4, pages 84-93. DOI: 10.5220/0004801500840093

in Bibtex Style

@conference{icaart14,
author={Junji Otsuka and Tomoharu Nagao},
title={Evolutionary Fuzzy Rule Construction for Iterative Object Segmentation},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2014},
pages={84-93},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004801500840093},
isbn={978-989-758-015-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Evolutionary Fuzzy Rule Construction for Iterative Object Segmentation
SN - 978-989-758-015-4
AU - Otsuka J.
AU - Nagao T.
PY - 2014
SP - 84
EP - 93
DO - 10.5220/0004801500840093