DYNAMIC PROGRAMMING APPROACH FOR SEMI-AUTOMATED ROAD EXTRACTION FROM MEDIUM- AND HIGH-RESOLUTION IMAGES

This paper presents a dynamic programming approach for semi-automated road extraction from medium- and high-resolution images. This method is a modified version of a pre-existent dynamic programming method for road extraction from low-resolution images. The basic assumption of this pre-existent method is that roads manifest as lines in low-resolution images and as such can be modelled and extracted as linear features. Contrary to this, roads manifest as ribbon features in medium- and high-resolution images and the goal of road extraction methods becomes the road centrelines. As a result, the original method can not accurately extract road centrelines from medium- and high- resolution images. In view of this, we propose a modification of merit function of the original approach, which is carried out by a constraint function embedding road edge properties. Preliminary results demonstrate the modified algorithm’s potential in extracting road centrelines from medium- and high-resolution images.

[1]  A. Gruen,et al.  Semi-Automatic Linear Feature Extraction by Dynamic Programming and LSB-Snakes , 1997 .

[2]  George Vosselman,et al.  Road tracing by profile matching and Kaiman filtering , 1995 .

[3]  Josiane Zerubia,et al.  New Prospects in Line Detection by Dynamic Programming , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Anthony Stefanidis,et al.  Uncertainty in Image-Based Change Detection , 2000 .

[5]  Gábor Székely,et al.  Ziplock Snakes , 1997, International Journal of Computer Vision.

[6]  Aviad Zlotnick,et al.  Finding Road Seeds in Aerial Images , 1993 .

[7]  Arcot Sowmya,et al.  Modelling and representation issues in automated feature extraction from aerial and satellite images , 2000 .

[8]  A. Dama,et al.  THE INTERNATIONAL ARCHIVES OF THE PHOTOGRAMMETRY, REMOTE SENSING AND SPATIAL INFORMATION SCIENCES ARCHIVES INTERNATIONALES DE PHOTOGRAMMÉTRIE, DE TÉLÉDÉTECTION ET DE SCIENCES DE L’INFORMATION SPATIALE INTERNATIONALES ARCHIV FÜR PHOTOGRAMMETRIE, FERNERKUNDUNG UND RAUMBEZOGENE INFORMATIONSWISSENS , 2004 .

[9]  David M. McKeown,et al.  Cooperative methods for road tracking in aerial imagery , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[10]  Ivan Laptev,et al.  Automatic extraction of roads from aerial images based on scale space and snakes , 2000 .

[11]  Martin A. Fischler,et al.  Detection of roads and linear structures in low-resolution aerial imagery using a multisource knowledge integration technique☆ , 1981 .

[12]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[13]  Ujjwal Maulik,et al.  SEMI-AUTOMATED FEATURE EXTRACTION USING SIMULATED ANNEALING , 2000 .

[14]  A. P. Dal Poza,et al.  ACTIVE TESTING AND EDGE ANALYSIS FOR ROAD CENTRELINE EXTRACTION , 2002 .