Mathematical foundations of evidence theory: a theory of reasoning with uncertain arguments
Mathematical models for handling partial knowledge in artificial intelligence
Allocation of arguments and evidence theory
Selected papers from the international workshop on Uncertainty in databases and deductive systems
Automatic object extraction from aerial imagery—a survey focusing on buildings
Computer Vision and Image Understanding
Segmentation of Color Textures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color image segmentation using fuzzy C-means and eigenspace projections
Signal Processing
Computers & Geosciences - Intelligent methods for processing geodata
MRF Clustering for segmentation of color images
Pattern Recognition Letters
A Box-Counting Approach to Color Segmentation
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
On Unsupervised Segmentation of Color Texture Images
HIPC '97 Proceedings of the Fourth International Conference on High-Performance Computing
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
State of the art on automatic road extraction for GIS update: a novel classification
Pattern Recognition Letters
A color texture based visual monitoring system for automatedsurveillance
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
An automatic system for urban road extraction from satellite and aerial images
WSEAS Transactions on Signal Processing
Applying local cooccurring patterns for object detection from aerial images
VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
Road network reconstruction for organizing paths
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Learning to detect roads in high-resolution aerial images
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Detection and matching of curvilinear structures
Pattern Recognition
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In this paper an efficient method for automatic road extraction in rural and semi-urban areas is presented. This work seeks the GIS update starting from color images and using preexisting vectorial information. As input data only the RGB bands of a satellite or aerial color image of high resolution is required. The system includes four different modules: data preprocessing; binary segmentation based on three levels of texture statistical evaluation; automatic vectorization by means of skeletal extraction; and finally a module for system evaluation. In the first module the color image is rectified and geo-referenced. The second module uses a new technique, named Texture Progressive Analysis (TPA), in order to obtain the segmented binary image. The TPA technique is developed in the evidence theory framework, and it consists in fusing information streaming from three different sources for the image. In the third module the obtained binary image is vectorized using an algorithm based on skeleton extraction techniques and morphological methods. The result is an extracted road network which is defined as a structural set of elements geometrically and topologically corrects. The fourth module is an evaluation of the procedure using a popular method. Experimental results show that this method is efficient in extracting and defining road networks from high resolution satellite and aerial imagery.