A Multi-Agent based Approach for Fuzzy Clustering of Large Image Data
Nashwa M. Abdelghaffar · ·; HewaydaM. S. Lotfy; Khamis, Soheir;
Abstract
Data clustering usually requires extensive
computations of similarity measures between dataset
members and cluster centers, especially for large datasets.
Image clustering can be an intermediate process in image
retrieval or segmentation, where a fast process is critically
required for large image databases. This paper introduces a
new approach of multi-agents for fuzzy image clustering
(MAFIC) to improve the time cost of the sequential fuzzy
c-means algorithm (FCM). The approach has the distinguished
feature of distributing the computation of cluster
centers and membership function among several parallel
agents, where each agent works independently on a different
sub-image of an image. Based on the Java Agent
Development Framework platform, an implementation of
MAFIC is tested on 24-bit large size images. The experimental
results show that the time performance of MAFIC
outperforms that of the sequential FCM algorithm by at
least four times, and thus reduces the time needed for the
clustering process.
computations of similarity measures between dataset
members and cluster centers, especially for large datasets.
Image clustering can be an intermediate process in image
retrieval or segmentation, where a fast process is critically
required for large image databases. This paper introduces a
new approach of multi-agents for fuzzy image clustering
(MAFIC) to improve the time cost of the sequential fuzzy
c-means algorithm (FCM). The approach has the distinguished
feature of distributing the computation of cluster
centers and membership function among several parallel
agents, where each agent works independently on a different
sub-image of an image. Based on the Java Agent
Development Framework platform, an implementation of
MAFIC is tested on 24-bit large size images. The experimental
results show that the time performance of MAFIC
outperforms that of the sequential FCM algorithm by at
least four times, and thus reduces the time needed for the
clustering process.
Other data
Title | A Multi-Agent based Approach for Fuzzy Clustering of Large Image Data | Authors | Nashwa M. Abdelghaffar · · ; HewaydaM. S. Lotfy ; Khamis, Soheir | Keywords | Image clustering Fuzzy c-means Multi-agent system | Issue Date | 17-Nov-2014 | Publisher | Springer | Journal | Journal of Real-Time Image Processing | DOI | 10.1007/s11554-014-0473-3 |
Attached Files
File | Description | Size | Format | |
---|---|---|---|---|
10.1007_s11554-014-0473-3.pdf | 1.72 MB | Adobe PDF | View/Open |
Similar Items from Core Recommender Database
Items in Ain Shams Scholar are protected by copyright, with all rights reserved, unless otherwise indicated.