Automatic Image Segmentation Optimized by Bilateral Filtering

Sanchez, Javier and Martínez Izquierdo, María Estíbaliz and Arquero Hidalgo, Águeda and Renza Torres, Diego (2010). Automatic Image Segmentation Optimized by Bilateral Filtering. In: "15th Iberoamerican Congress on Pattern Recognition, CIARP 2010", 08/11/2010 - 11/11/2010, Sao Paulo, Brasil. ISBN 978-3-642-16686-0.

Description

Title: Automatic Image Segmentation Optimized by Bilateral Filtering
Author/s:
  • Sanchez, Javier
  • Martínez Izquierdo, María Estíbaliz
  • Arquero Hidalgo, Águeda
  • Renza Torres, Diego
Item Type: Presentation at Congress or Conference (Article)
Event Title: 15th Iberoamerican Congress on Pattern Recognition, CIARP 2010
Event Dates: 08/11/2010 - 11/11/2010
Event Location: Sao Paulo, Brasil
Title of Book: Proceedings of the 15th Iberoamerican Congress on Pattern Recognition, CIARP 2010
Date: November 2010
ISBN: 978-3-642-16686-0
Volume: 6419
Subjects:
Freetext Keywords: Image segmentation, Bilateral filter, Self-calibrating framework.
Faculty: Facultad de Informática (UPM)
Department: Arquitectura y Tecnología de Sistemas Informáticos
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

The object-based methodology is one of the most commonly used strategies for processing high spatial resolution images. A prerequisite to object-based image analysis is image segmentation, which is normally defined as the subdivision of an image into separated regions. This study proposes a new image segmentation methodology based on a self-calibrating multi-band region growing approach. Two multispectral aerial images were used in this study. The unsupervised image segmentation approach begins with a first step based on a bidirectional filtering, in order to eliminate noise, smooth the initial image and preserve edges. The results are compared with ones obtained from Definiens Developper software.

More information

Item ID: 7086
DC Identifier: http://oa.upm.es/7086/
OAI Identifier: oai:oa.upm.es:7086
Official URL: http://www.springerlink.com/content/1v771g21h3u03741/
Deposited by: Memoria Investigacion
Deposited on: 24 May 2011 13:25
Last Modified: 20 Apr 2016 16:12
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