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8 November 2012 A new approach to automatic road extraction from satellite images using boosted classifiers
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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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Umut Çinar, Ersin Karaman, Ekin Gedik, Yasemin Yardımcı, and Uğur Halıcı "A new approach to automatic road extraction from satellite images using boosted classifiers", Proc. SPIE 8537, Image and Signal Processing for Remote Sensing XVIII, 85370O (8 November 2012); https://doi.org/10.1117/12.974693
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