Road Extraction in Suburban Areas Based on Normalized Cuts
نویسنده
چکیده
This paper deals with road extraction of high resolution aerial images of suburban scenes based on segmentation using the Normalized Cuts algorithm. The aim of our project is the extraction of roads for the assessment of a road database, however, this paper is restricted to road extraction. The segmentation as our basic step is designed to yield a good division between road areas and the surroundings. We use the Normalized Cuts algorithm, which is a graph-based approach that divides the image on the basis of pixel similarities. The definition of these similarities can incorporate several features, which is necessary for the segmentation in complex surroundings such as built-up areas. The features used for segmentation comprise colour, hue, edges and road colour derived with prior information about the position of the centerline from the database. The initial segments have to be grouped due to an enforced oversegmentation. The grouping is based on the criteria of mean colour difference, edge strength of the shared borders and colour standard deviation of merged initial segments. The grouped segments are then evaluated using shape criteria in order to extract road parts. Results on some test images show that the approach provides reliable road parts. Concluding remarks are given at the end to point out further investigations concerning the evaluation of the road segments and their use in database assessment. * Corresponding author.
منابع مشابه
Road Extraction for the Update of Road Databases in Suburban Areas
This paper deals with road extraction in suburban areas from high resolution aerial images. The extraction results are intended to be used for updating a road database. The road extraction algorithm follows a region-based approach in which the image is first segmented using the normalized cuts algorithm with colour and edge criteria. Then, the initial segments are grouped to larger segments in ...
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