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Proceedings Paper

A new approach to automatic road extraction from satellite images using boosted classifiers
Author(s): Umut Çinar; Ersin Karaman; Ekin Gedik; Yasemin Yardımcı; Uğur Halıcı
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Paper Abstract

In this study, a supervised method for automatic road detection based on spectral indices and structural properties is proposed. The need of generalizing the spectral features for the images captured by different kinds of devices is investigated. Mean-shift segmentation algorithm is employed to partition the input multi-spectral image in addition to k-means which is used as a complementary method for structural feature generation. Adaboost learning algorithm is utilized with extracted features to distinguish roads from non-road regions in the satellite images. The proposed algorithm is tested on an image database containing both IKONOS and GEOEYE images to verify the achieved generalization. The empirical results show that the proposed road extraction method is promising and capable of finding the majority of the road network.

Paper Details

Date Published: 8 November 2012
PDF: 10 pages
Proc. SPIE 8537, Image and Signal Processing for Remote Sensing XVIII, 85370O (8 November 2012); doi: 10.1117/12.974693
Show Author Affiliations
Umut Çinar, Middle East Technical Univ. (Turkey)
Ersin Karaman, Middle East Technical Univ. (Turkey)
Ekin Gedik, Middle East Technical Univ. (Turkey)
Yasemin Yardımcı, Middle East Technical Univ. (Turkey)
Uğur Halıcı, Middle East Technical Univ. (Turkey)

Published in SPIE Proceedings Vol. 8537:
Image and Signal Processing for Remote Sensing XVIII
Lorenzo Bruzzone, Editor(s)

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