Tubularity Tracking Based Automatic Road Detection from Sattelite Images

In this paper, a novel approach based on tubularity tracking and graph cuts for road detection from satellites images is presented. The most important feature of the proposed method is its local peak detection filter. Unlike the tubularity based road or road like curvilinear structure detection methods presented in the literature, proposed method samples local peaks from tubularity image by tracking the peak points based on Bayesian filtering in order to construct graphs and introduces no significant computational complexity.
22nd IEEE Signal Processing and Communications Applications Conference (SIU)


Junction extraction on road masks by pruned skeletons
Cinar, UMUT; KARAMAN, ERSİN; GEDİK, Ekin; ÇETİN, YASEMİN; Halıcı, Uğur (2012-09-26)
This study proposes a new method to detect road junctions from existing road masks obtained from geospatial databases. Moreover, this method can be used to extract junction points from the road masks generated by automatic or semiautomatic road extraction algorithms. The algorithm is intended to lower the false detection rate by refining the input road mask. Vector space analysis of the pruned road skeleton provides a simple yet robust detection and classification strategy. Empirical results demonstrate the...
Road network extraction from high-resolution multi spectral satellite images
Karaman, Ersin; Çetin, Yasemin; Department of Information Systems (2012)
In this thesis, an automatic road extraction algorithm for multi-spectral images is developed. The developed model extracts elongated structures from images by using edge detection, segmentation and clustering techniques. The study also extracts non-road regions like vegetative fields, bare soils and water bodies to obtain more accurate road map. The model is constructed in a modular approach that aims to extract roads with different characteristics. Each module output is combined to create a road score map...
Sea Detection on High-Resolution Panchromatic Satellite Images Using Texture and Intensity
Besbinar, Beril; Alatan, Abdullah Aydın (2014-01-01)
In this paper, a two-stage sea-land mask detection algorithm on high resolution panchromatic images is proposed. An initial mask is generated using texture features in the first stage and this mask is refined by using intensity values in the second stage. Image is divided into windows and the Local Binary Patterns (LBP) histograms, evaluated at each window, are modelled using the sea and land sample spaces obtained by the altitude information which has very low resolution compared to the image. These models...
Robust Automatic Target Recognition in FLIR imagery
Soyman, Yusuf (2012-04-24)
In this paper, a robust automatic target recognition algorithm in FLIR imagery is proposed. Target is first segmented out from the background using wavelet transform. Segmentation process is accomplished by parametric Gabor wavelet transformation. Invariant features that belong to the target, which is segmented out from the background, are then extracted via moments. Higher-order moments, while providing better quality for identifying the image, are more sensitive to noise. A trade-off study is then perform...
Road extraction from satellite images by self supervised classification and perceptual grouping
Şahin, Eda; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2013)
Road network extraction from high resolution satellite imagery is the most frequently utilized technique for updating and correcting geographic information system (GIS) databases, registering multi-temporal images for change detection and automatically aligning spatial datasets. This advance method is widely employed due to the improvements in satellite technology such as development of new sensors for high resolution imagery. To avoid the cost of the human interaction, various automatic and semi-automatic ...
Citation Formats
Y. Z. Gürbüz and A. A. Alatan, “Tubularity Tracking Based Automatic Road Detection from Sattelite Images,” presented at the 22nd IEEE Signal Processing and Communications Applications Conference (SIU), Karadeniz Teknik Univ, Trabzon, Turkey, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55017.