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Reseach Article

Land Cover Feature Extraction and Analysis using Biogeography based Optimization (BBO) Algorithm

by Prabhjot Kaur, Kamaljit Kaur Dhillon, Rajdeep Singh Chauhan, Savneet Kaur
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 97 - Number 20
Year of Publication: 2014
Authors: Prabhjot Kaur, Kamaljit Kaur Dhillon, Rajdeep Singh Chauhan, Savneet Kaur
10.5120/17126-7769

Prabhjot Kaur, Kamaljit Kaur Dhillon, Rajdeep Singh Chauhan, Savneet Kaur . Land Cover Feature Extraction and Analysis using Biogeography based Optimization (BBO) Algorithm. International Journal of Computer Applications. 97, 20 ( July 2014), 28-31. DOI=10.5120/17126-7769

@article{ 10.5120/17126-7769,
author = { Prabhjot Kaur, Kamaljit Kaur Dhillon, Rajdeep Singh Chauhan, Savneet Kaur },
title = { Land Cover Feature Extraction and Analysis using Biogeography based Optimization (BBO) Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 97 },
number = { 20 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 28-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume97/number20/17126-7769/ },
doi = { 10.5120/17126-7769 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:24:40.475975+05:30
%A Prabhjot Kaur
%A Kamaljit Kaur Dhillon
%A Rajdeep Singh Chauhan
%A Savneet Kaur
%T Land Cover Feature Extraction and Analysis using Biogeography based Optimization (BBO) Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 97
%N 20
%P 28-31
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The entropy vector is used to identify the homogeneity between the regions but in this proposed approach we are using a wavelet inspired segmented approach for the region match so that more clearly differentiate the homogenous and heterogeneous regions over the image. In this existing work, the K-means clustering is used as the initial classification and then the BBO is implemented. An initial segmented analysis is implemented to identify the number of classes more accurately and then the classification is performed. The main objective of the work is to perform the region classification for the land cover images development and implement wavelet inspired BBO approach to perform the classification process. The initial segmentation based similarity measure is performed to identify the number of classes using Clustering method and then the clustering process is done using Cmeans. The major objective of the work is to define more efficient classification under different regions.

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Index Terms

Computer Science
Information Sciences

Keywords

Image Segmentation BBO K-Means Clustering