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Automated extraction of road network from medium-and high-resolution images

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Abstract

This paper presents an automatic methodology for road network extraction from medium-and high-resolution aerial images. It is based on two steps. In the first step, the road seeds (i.e., road segments) are extracted using a set of four road objects and another set of connection rules among road objects. Each road object is a local representation of an approximately straight road fragment and its construction is based on a combination of polygons describing all relevant image edges, according to some rules embodying road knowledge. Each road seed is composed by a sequence of connected road objects in which each sequence of this type can be geometrically structured as a chain of contiguous quadrilaterals. In the second step, two strategies for road completion are applied in order to generate the complete road network. The first strategy is based on two basic perceptual grouping rules, i.e., proximity and collinearity rules, which allow the sequential reconstruction of gaps between every pair of disconnected road segments. This strategy does not allow the reconstruction of road crossings, but it allows the extraction of road centerlines from the contiguous quadrilaterals representing connected road segments. The second strategy for road completion aims at reconstructing road crossings. Firstly, the road centerlines are used to find reference points for road crossings, which are their approximate positions. Then these points are used to extract polygons representing the contours of road crossings. This paper presents the proposed methodology and experimental results.

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Authors and Affiliations

  1. Department of Cartography, Rua Roberto Simonsen, São Paulo State University, 305, 19060-900, Presidente Prudente, SP, Brazil

    A. P. Dal Poz, R. B. Zanin & G. M. do Vale

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  1. A. P. Dal Poz
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  2. R. B. Zanin
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  3. G. M. do Vale
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Additional information

The text was submitted by the authors in English.

Aluir Porfirio Dal Poz. Year of birth: 1960. Year of graduation/Name of the institution: 1987 (Cartographic Engineering)/Sao Paulo State University. Year in which an academic degree was awarded: M.Sc. degree in Geodetic Science at Parana Federal University: 1991. Ph.D. degree in Engineering at Sao Paulo University: 1996. Affiliation: Sao Paulo State University. Position: Associate Professor. Area of research: Digital Photogrammetry and Image Analysis. Number of publications: 5 Book Chapters, 25 in Journals, and 75 in Proceedings. Membership to academies: Scientific societies: Brazilian Society of Cartography, Brazilian Society of Applied and Computational Mathematics, and Canadian Institute of Geomatics. Editorial boards and journals: Associate Editor of the Series in Geodetic Science and member of the editorial board of Brazilian Journal of Cartography. Awards and prizes for achievements in research or applications: Scientific Beginner in Cartography (1995) and Cartographic Merit (1999), both awarded by Brazilian Society of Cartography.

Rodrigo Bruno Zanin. Year of birth: 1976. Year of graduation/Name of the institution: 2000 (Mathematics)/Sao Paulo State University. Year in which an academic degree was awarded: M.Sc. degree in Cartographic Sciences at Sao Paulo State University: 2004. Affiliation: Sao Paulo State University. Position: Ph.D. Candidate. Area of research: Digital Photogrammetry and Image Analysis. Number of publications: 2 in Journals and 5 in Proceedings.

Giovane Maia do Vale. Year of birth: 1969. Year of graduation/Name of the institution: 1998 (Mathematics)/Sao Paulo State University. Year in which an academic degree was awarded: M.Sc. degree in Cartographic Sciences at Sao Paulo State University: 2003. Affiliation: Sao Paulo State University. Position: Ph.D. Candidate. Area of research: Digital Photogrammetry and Image Analysis. Number of publications: 3 in Journals and 10 in Proceedings. Membership to academies: Scientific societies: Brazilian Society of Applied and Computational Mathematics.

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Dal Poz, A.P., Zanin, R.B. & do Vale, G.M. Automated extraction of road network from medium-and high-resolution images. Pattern Recognit. Image Anal. 16, 239–248 (2006). https://doi.org/10.1134/S1054661806020118

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