IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection and Linear Feature Extraction Using a 2-D Random Field Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian multiple-hypothesis approach to edge grouping and contour segmentation
International Journal of Computer Vision
An application of heuristic search methods to edge and contour detection
Communications of the ACM
Fast, Accurate and Consistent Modeling of Drainage andSurrounding Terrain
International Journal of Computer Vision
Orientation Space Filtering for Multiple Orientation Line Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Coarse-to-Fine Dynamic Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Semi-Automated Extraction of Rivers from Digital Imagery
Geoinformatica
Recognizing marbling in dry-cured Iberian ham by multiscale analysis
Pattern Recognition Letters
A Gibbs Point Process for Road Extraction from Remotely Sensed Images
International Journal of Computer Vision
Point Processes for Unsupervised Line Network Extraction in Remote Sensing
IEEE Transactions on Pattern Analysis and Machine Intelligence
A robust dynamic programming algorithm to extract skyline in images for navigation
Pattern Recognition Letters
G-wire: A livewire segmentation algorithm based on a generalized graph formulation
Pattern Recognition Letters
International Journal of Computer Vision
Higher-Order Active Contour Energies for Gap Closure
Journal of Mathematical Imaging and Vision
WSEAS Transactions on Computers
Fast curvilinear structure extraction and delineation using density estimation
Computer Vision and Image Understanding
Feature extraction method for land consolidation from high resolution imagery
WSEAS Transactions on Information Science and Applications
MATH'08 Proceedings of the 13th WSEAS international conference on Applied mathematics
Detection of Linear Structures in Remote-Sensed Images
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Prediction and change detection in sequential data for interactive applications
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
A robust approach for automatic detection and segmentation of cracks in underground pipeline images
Image and Vision Computing
Unsupervised line network extraction in remote sensing using a polyline process
Pattern Recognition
Extended Phase Field Higher-Order Active Contour Models for Networks
International Journal of Computer Vision
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Graph cuts approach to MRF based linear feature extraction in satellite images
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Stroke extraction in cartoon images using edge-enhanced isotropic nonlinear filter
Proceedings of the 9th ACM SIGGRAPH Conference on Virtual-Reality Continuum and its Applications in Industry
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
FoSA: F* Seed-growing Approach for crack-line detection from pavement images
Image and Vision Computing
Asymmetric inexact matching of spatially-attributed graphs
GbRPR'05 Proceedings of the 5th IAPR international conference on Graph-Based Representations in Pattern Recognition
Urban road extraction from high-resolution optical satellite images
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
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The detection of lines in satellite images has drawn a lot of attention within the last 15 years. Problems of resolution, noise, and image understanding are involved, and one of the best methods developed so far is the F* algorithm of Fischler, which achieves robustness, rightness, and rapidity. Like other methods of dynamic programming, it consists of defining a cost which depends on local information; then a summation-minimization process in the image is performed. We present herein a mathematical formalization of the F* algorithm, which allows us to extend the cost both to cliques of more than two points (to deal with the contrast), and to neighborhoods of size larger than one (to take into account the curvature). Thus, all the needed information (contrast, grey-level, curvature) is synthesized in a unique cost function defined on the digital original image. This cost is used to detect roads and valleys in satellite images (SPOT).