Scaling Theorems for Zero Crossings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Uniqueness of the Gaussian Kernel for Scale-Space Filtering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision, Graphics, and Image Processing
Trace Inference, Curvature Consistency, and Curve Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space for Discrete Signals
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Junction classification by multiple orientation detection
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
New Prospects in Line Detection by Dynamic Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Unbiased Detector of Curvilinear Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Curve Segmentation Under Partial Occlusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Deformable Kernels for Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure and Motion from Line Segments in Multiple Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimating Motion and Structure from Correspondences of Line Segments between Two Perspective Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonparametric Segmentation of Curves into Various Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian Multiple Hypothesis Approach to Contour Grouping
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Detection of General Edges and Keypoints
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Steerable-Scalable Kernels for Edge Detection and Junction Analysis
ECCV '92 Proceedings of the Second European Conference on Computer Vision
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Measuring Microcirculation Using Spatiotemporal Image Analysis
CVRMed '95 Proceedings of the First International Conference on Computer Vision, Virtual Reality and Robotics in Medicine
Edge Detection and Ridge Detection with Automatic Scale Selection
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Orientation Space Filtering for Multiple Orientation Line Segmentation
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Multiscale detection of curvilinear structures in 2-D and 3-D image data
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Invariant Feature Extraction and Object Shape Matching Using Gabor Filtering
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Segmentation of brush strokes by saliency preserving dual graph contraction
Pattern Recognition Letters - Special issue: Graph-based representations in pattern recognition
A review of vessel extraction techniques and algorithms
ACM Computing Surveys (CSUR)
A Neural Network Based Framework for Directional Primitive Extraction
Neural Processing Letters
3-D Extraction of Fibres from Microtomographic Images of Fibre-Reinforced Composite Materials
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
Crossing-Preserving Coherence-Enhancing Diffusion on Invertible Orientation Scores
International Journal of Computer Vision
Unbiased extraction of lines with parabolic and Gaussian profiles
Computer Vision and Image Understanding
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The goal of this paper is to present an appropriate method for the segmentation of lines at intersections (X-junctions) and branches (T-junctions), which can be regarded as local regions where lines occur at multiple orientations. A novel representation called 驴orientation space驴 is proposed, which is derived by adding the orientation axis to the abscissa and the ordinate of the image. The orientation space representation is constructed by treating the orientation parameter, to which Gabor filters can be tuned, as a continuous variable. The problem of segmenting lines at multiple orientations is dealt with by thresholding 3D imagesin the orientation space and then detecting the connected components therein. In this way, X-junctions and T-junctions can be separated effectively. Curve grouping can also be accomplished. The segmentation of mathematically modeled X-, T-, and L-junctions is demonstrated and analyzed. The sensitivity limits of the method are also discussed. Experimental results using both synthesized and real images show the method to be effective for junction segmentation and curve grouping.