A hybrid FPAB/BBO Algorithm for Satellite Image Classification

In the past years, remote sensing has been used for the classification of satellite image on a very large scale. This paper deals with image classification by using swarm computing technique. In this work, we use a new swarm data clustering method based upon flower pollination by artificial bees to...

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Bibliographic Details
Published in:International journal of computer applications 2010-09, Vol.6 (5), p.31-36
Main Authors: Johal, Navdeep Kaur, Singh, Samandeep, Kundra, Harish
Format: Article
Language:English
Subjects:
Algorithms
Classification
Clustering
Clusters
Data points
Image classification
Satellites
Self-similarity
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Summary:In the past years, remote sensing has been used for the classification of satellite image on a very large scale. This paper deals with image classification by using swarm computing technique. In this work, we use a new swarm data clustering method based upon flower pollination by artificial bees to cluster the satellite image pixels. The aim of clustering is to separate a set of data points into self-similar groups. Those clusters will be further classified using Biogeography Based Optimization. The results indicate that highly accurate classification of the satellite image is obtained by using the proposed algorithm.
ISSN:0975-8887
0975-8887
DOI:10.5120/1074-1403