Circular object recognition from satellite images

Hind Taud; Juan Carlos Herrera-Lozada; Jesus Antonio Alvarez-Cedillo; Magdalena Marciano-Melchor; Ramon Silva-Ortigoza; Mauricio Olguin-Carbajal

doi:10.1109/IGARSS.2012.6351029

Circular object recognition from satellite images

Hind Taud, Juan Carlos Herrera-Lozada, Jesus Antonio Alvarez-Cedillo, Magdalena Marciano-Melchor, Ramon Silva-Ortigoza, Mauricio Olguin-Carbajal

Centro de Innovación y Desarrollo Tecnológico en Cómputo (CIDETEC)
Unidad Profesional Interdisciplinaria de Ingeniería y Ciencias Sociales y Administrativas (UPIICSA)

Research output: Contribution to conference › Paper › peer-review

1 Scopus citations

Abstract

Pattern recognition has been the object of interest for many researchers in different fields. In remote sensing, geo-spatial patterns such as circular structures can be observed from satellite imagery and aerial photographs. Recognizing circular structures is difficult in remote sensing imagery. In this article, a detection method of circular forms in satellite image is investigated. Based on Adaboost and Haar features, the method is a machine learning technique. Training data sets are extracted from GoogleEarth. Experiments and results are provided.

Original language	English
Pages	2324-2327
Number of pages	4
DOIs	https://doi.org/10.1109/IGARSS.2012.6351029
State	Published - 2012
Event	2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 - Munich, Germany Duration: 22 Jul 2012 → 27 Jul 2012

Conference

Conference	2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012
Country/Territory	Germany
City	Munich
Period	22/07/12 → 27/07/12

Keywords

Adaboost
Haar features
circular
learning technique
pattern recognition

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10.1109/IGARSS.2012.6351029

Cite this

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title = "Circular object recognition from satellite images",

abstract = "Pattern recognition has been the object of interest for many researchers in different fields. In remote sensing, geo-spatial patterns such as circular structures can be observed from satellite imagery and aerial photographs. Recognizing circular structures is difficult in remote sensing imagery. In this article, a detection method of circular forms in satellite image is investigated. Based on Adaboost and Haar features, the method is a machine learning technique. Training data sets are extracted from GoogleEarth. Experiments and results are provided.",

keywords = "Adaboost, Haar features, circular, learning technique, pattern recognition",

author = "Hind Taud and Herrera-Lozada, {Juan Carlos} and Alvarez-Cedillo, {Jesus Antonio} and Magdalena Marciano-Melchor and Ramon Silva-Ortigoza and Mauricio Olguin-Carbajal",

year = "2012",

doi = "10.1109/IGARSS.2012.6351029",

language = "Ingl{\'e}s",

pages = "2324--2327",

note = "2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012 ; Conference date: 22-07-2012 Through 27-07-2012",

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TY - CONF

T1 - Circular object recognition from satellite images

AU - Taud, Hind

AU - Herrera-Lozada, Juan Carlos

AU - Alvarez-Cedillo, Jesus Antonio

AU - Marciano-Melchor, Magdalena

AU - Silva-Ortigoza, Ramon

AU - Olguin-Carbajal, Mauricio

PY - 2012

Y1 - 2012

N2 - Pattern recognition has been the object of interest for many researchers in different fields. In remote sensing, geo-spatial patterns such as circular structures can be observed from satellite imagery and aerial photographs. Recognizing circular structures is difficult in remote sensing imagery. In this article, a detection method of circular forms in satellite image is investigated. Based on Adaboost and Haar features, the method is a machine learning technique. Training data sets are extracted from GoogleEarth. Experiments and results are provided.

AB - Pattern recognition has been the object of interest for many researchers in different fields. In remote sensing, geo-spatial patterns such as circular structures can be observed from satellite imagery and aerial photographs. Recognizing circular structures is difficult in remote sensing imagery. In this article, a detection method of circular forms in satellite image is investigated. Based on Adaboost and Haar features, the method is a machine learning technique. Training data sets are extracted from GoogleEarth. Experiments and results are provided.

KW - Adaboost

KW - Haar features

KW - circular

KW - learning technique

KW - pattern recognition

UR - http://www.scopus.com/inward/record.url?scp=84873150828&partnerID=8YFLogxK

U2 - 10.1109/IGARSS.2012.6351029

DO - 10.1109/IGARSS.2012.6351029

M3 - Artículo

SP - 2324

EP - 2327

T2 - 2012 32nd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2012

Y2 - 22 July 2012 through 27 July 2012

ER -

Circular object recognition from satellite images

Abstract

Conference

Keywords

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