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Authors: Luiz Carlos A. M. Cavalcanti 1 ; Jose Reginaldo Hughes Carvalho 2 and Eulanda Miranda dos Santos 2

Affiliations: 1 Nokia Institute of Technology and Universidade Federal do Amazonas, Brazil ; 2 Universidade Federal do Amazonas, Brazil

Keyword(s): Semantic Segmentation, Image Processing, Machine Learning, Classification.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis ; Segmentation and Grouping

Abstract: Segmentation is one of the most important operations in Computer Vision. Partition of the image in several domain-independent components is important in several practical machine learning solutions involving visual data. In the specific problem of finding anomalies in aerial images of forest regions, this can be specially important, as a multilevel classification solution can demand that each type of terrain and other components of the image are inspected by different classification algorithms or parameters. This work compares several common classification algorithms and assess their reliability on segmenting aerial images of rain forest regions as a first step into a multi-level classification solution. Finally, we draw conclusions based on the experiments using real images from a publicly available dataset, comparing the results of those classification algorithms for segmenting this kind of images.

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Paper citation in several formats:
A. M. Cavalcanti, L.; Hughes Carvalho, J. and Miranda dos Santos, E. (2015). A Comparison on Supervised Machine Learning Classification Techniques for Semantic Segmentation of Aerial Images of Rain Forest Regions. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 2: VISAPP; ISBN 978-989-758-089-5; ISSN 2184-4321, SciTePress, pages 498-504. DOI: 10.5220/0005300004980504

@conference{visapp15,
author={Luiz Carlos {A. M. Cavalcanti}. and Jose Reginaldo {Hughes Carvalho}. and Eulanda {Miranda dos Santos}.},
title={A Comparison on Supervised Machine Learning Classification Techniques for Semantic Segmentation of Aerial Images of Rain Forest Regions},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 2: VISAPP},
year={2015},
pages={498-504},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005300004980504},
isbn={978-989-758-089-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 2: VISAPP
TI - A Comparison on Supervised Machine Learning Classification Techniques for Semantic Segmentation of Aerial Images of Rain Forest Regions
SN - 978-989-758-089-5
IS - 2184-4321
AU - A. M. Cavalcanti, L.
AU - Hughes Carvalho, J.
AU - Miranda dos Santos, E.
PY - 2015
SP - 498
EP - 504
DO - 10.5220/0005300004980504
PB - SciTePress

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