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An Interactive Technique for Cartographic Feature Extraction from Aerial and Satellite Image Sensors

In this paper, an interactive technique for extracting cartographic features from aerial and spatial images is presented. The method is essentially an interactive method of image region segmentation based on pixel grey level and texture information. The underlying segmentation method is seeded regio...

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Detalles Bibliográficos
Autores principales: Kicherer, Stefan, Malpica, Jose A., Alonso, Maria C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3705472/
https://www.ncbi.nlm.nih.gov/pubmed/27873786
http://dx.doi.org/10.3390/s8084786
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author Kicherer, Stefan
Malpica, Jose A.
Alonso, Maria C.
author_facet Kicherer, Stefan
Malpica, Jose A.
Alonso, Maria C.
author_sort Kicherer, Stefan
collection PubMed
description In this paper, an interactive technique for extracting cartographic features from aerial and spatial images is presented. The method is essentially an interactive method of image region segmentation based on pixel grey level and texture information. The underlying segmentation method is seeded region growing. The criterion for growing regions is based on both texture and grey level, where texture is quantified using co-occurrence matrices. The Kullback distance is utilised with co-occurrence matrices in order to describe the image texture, then the Theory of Evidence is applied to merge the information coming from texture and grey level image from the RGB bands. Several results from aerial and spatial images that support the technique are presented
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spelling pubmed-37054722013-07-09 An Interactive Technique for Cartographic Feature Extraction from Aerial and Satellite Image Sensors Kicherer, Stefan Malpica, Jose A. Alonso, Maria C. Sensors (Basel) Article In this paper, an interactive technique for extracting cartographic features from aerial and spatial images is presented. The method is essentially an interactive method of image region segmentation based on pixel grey level and texture information. The underlying segmentation method is seeded region growing. The criterion for growing regions is based on both texture and grey level, where texture is quantified using co-occurrence matrices. The Kullback distance is utilised with co-occurrence matrices in order to describe the image texture, then the Theory of Evidence is applied to merge the information coming from texture and grey level image from the RGB bands. Several results from aerial and spatial images that support the technique are presented Molecular Diversity Preservation International (MDPI) 2008-08-19 /pmc/articles/PMC3705472/ /pubmed/27873786 http://dx.doi.org/10.3390/s8084786 Text en © 2008 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/).
spellingShingle Article
Kicherer, Stefan
Malpica, Jose A.
Alonso, Maria C.
An Interactive Technique for Cartographic Feature Extraction from Aerial and Satellite Image Sensors
title An Interactive Technique for Cartographic Feature Extraction from Aerial and Satellite Image Sensors
title_full An Interactive Technique for Cartographic Feature Extraction from Aerial and Satellite Image Sensors
title_fullStr An Interactive Technique for Cartographic Feature Extraction from Aerial and Satellite Image Sensors
title_full_unstemmed An Interactive Technique for Cartographic Feature Extraction from Aerial and Satellite Image Sensors
title_short An Interactive Technique for Cartographic Feature Extraction from Aerial and Satellite Image Sensors
title_sort interactive technique for cartographic feature extraction from aerial and satellite image sensors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3705472/
https://www.ncbi.nlm.nih.gov/pubmed/27873786
http://dx.doi.org/10.3390/s8084786
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