Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/13967
Title: Automatic vegetation identification and building detection from a single nadir aerial image
Authors: Shorter, Nicholas 
Kasparis, Takis 
Major Field of Science: Engineering and Technology
Field Category: Civil Engineering
Keywords: Building detection;Color invariants;Nadir aerial image;Vegetation identification
Issue Date: 16-Oct-2009
Source: Remote Sens. 2009, vol. 1, no.4, pp.731-757
Volume: 1
Issue: 4
Start page: 731
End page: 757
Journal: Remote Sensing 
Abstract: A novel, automatic tertiary classifier is proposed for identifying vegetation, building and non-building objects from a single nadir aerial image. The method is unsupervised, that is, no parameter adjustment is done during the algorithm's execution. The only assumption the algorithm makes about the building structures is that they have convex rooftop sections. Results are provided for two different actual data sets. © 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.
ISSN: 20724292
DOI: 10.3390/rs1040731
Rights: © 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland. This article is an open–access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
Type: Article
Affiliation : University of Central Florida 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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