Road extraction from satellite images by self-supervised classification and perceptual grouping

Sahin, E.
Ulusoy, İlkay
A fully automatized method which can extract road networks by using the spectral and structural features of the roads is proposed. First, Anti-parallel Centerline Extraction (ACE) is used to obtain road seed points. Then, the road seeds are improved with perceptual grouping method and the road class is determined with Maximum Likelihood Estimation (MLE) by modeling the seed points with Gaussian Mixture. The morphological operations (opening, closing and thinning) are performed for improving classification results and determining the road topology roughly. Finally, perceptual grouping is performed for removing non-road line segments and filling the gaps on the topology. The proposed algorithm is tested on 1 meter resolution IKONOS images and results better than previous algorithms are obtained


Road extraction from high-resolution satellite images
Özkaya, Meral; Temizel, Alptekin; Department of Information Systems (2009)
Roads are significant objects of an infrastructure and the extraction of roads from aerial and satellite images are important for different applications such as automated map generation and change detection. Roads are also important to detect other structures such as buildings and urban areas. In this thesis, the road extraction approach is based on Active Contour Models for 1- meter resolution gray level images. Active Contour Models contains Snake Approach. During applications, the road structure was sepa...
Road extraction from high resolution satellite images using adaptive boosting with multi-resolution analysis
Çınar, Umut; Çetin, Yasemin; Department of Information Systems (2012)
Road extraction from satellite or aerial imagery is a popular topic in remote sensing, and there are many road extraction algorithms suggested by various researches. However, the need of reliable remotely sensed road information still persists as there is no sufficiently robust road extraction algorithm yet. In this study, we explore the road extraction problem taking advantage of the multi-resolution analysis and adaptive boosting based classifiers. That is, we propose a new road extraction algorithm explo...
Beforehand obtaining a safety operation condition by using daily load curves in transient stability and graphical software for transient stability applications
Öztop, Celal; Ertaş, Arif; Department of Electrical and Electronics Engineering (2005)
In this thesis, relationship between two most important transient stability indices, critical clearing time and generator rotor angle is examined for one machine-infinite bus system and then extended to the multimachine case and is observed to be linear. By using the linear relationship between critical clearing time and generator rotor angle and utilizing the daily load curve, a new preventive method is proposed. The aim of this method is to make all critical clearing times longer than the relay and circui...
Building Detection in satellite images by textural features and Adaboost
CETIN, MELIH; Halıcı, Uğur (2010-08-24)
A method based on textural features and Adaboost for detecting buildings in satellite images is proposed. Several local textural features including mean and standard deviation of image intensity and gradient, Zernike moments, Circular-Mellin features, Haralick features, Fourier Power Spectrum, Wavelets, Gabor Filters, and a set features extracted from HSV color space are extracted. Adaboost learning algorithm is employed for both classification and determining the beneficial feature subset, due to its featu...
Parallel implementation of a gas-kinetic BGK method on unstructured grids for 3-D inviscid missile flows
Ilgaz, Murat; Tuncer, İsmail Hakkı (2009-10-12)
A 3-D gas-kinetic BGK method and its parallel solution algorithm are developed for the computation of inviscid missile flows on unstructured grids. Flow solutions over a supersonic missile are presented to validate the accuracy and robustness of the method. It is shown that the computation time, which is an important deficiency of gas-kinetic BGK methods, may significantly be reduced by performing computations in parallel. © 2009 Springer-Verlag Berlin Heidelberg.
Citation Formats
E. Sahin and İ. Ulusoy, “Road extraction from satellite images by self-supervised classification and perceptual grouping,” 2013, vol. 8892, Accessed: 00, 2020. [Online]. Available: