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 |
Files in This Item:
File | Description | Size | Format | |
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remotesensing-01-00731.pdf | Fulltext | 1.7 MB | Adobe PDF | View/Open |
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