UGC Approved Journal no 63975(19)

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Published in:

Volume 6 Issue 2
February-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRAB06149


Registration ID:
197766

Page Number

789-794

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Title

HSV Color Histogram based Land Cover Classification of Remotely Sensed Data using different Classifiers

Abstract

Land cover classification of remotely sensed images is the basis for many environmental and socio economic applications. Feature extraction plays a vital role in multispectral remote sensing image classification before classifying the image. In this paper, color features are extracted using HSV color histogram model to classify the land cover. The extracted features are trained and tested by supervised classifiers such as K Nearest neighbor, Decision Tree, RUSBoost, Random Forest, Support vector machine and Naive Bayes classifiers. The performance of the classifiers is compared based on the metrics accuracy and kappa coefficient. An IRS LISS IV orthorectified dataset is chosen as the input image for this experiment. It is observed that the random forest classifier outperformed when compared to other classifiers.

Key Words

HSV Color Histogram based Land Cover Classification of Remotely Sensed Data using different Classifiers

Cite This Article

"HSV Color Histogram based Land Cover Classification of Remotely Sensed Data using different Classifiers ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.789-794, February-2019, Available :http://www.jetir.org/papers/JETIRAB06149.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"HSV Color Histogram based Land Cover Classification of Remotely Sensed Data using different Classifiers ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp789-794, February-2019, Available at : http://www.jetir.org/papers/JETIRAB06149.pdf

Publication Details

Published Paper ID: JETIRAB06149
Registration ID: 197766
Published In: Volume 6 | Issue 2 | Year February-2019
DOI (Digital Object Identifier):
Page No: 789-794
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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