On the Detection of Dominant Points on Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Context-free attentional operators: the generalized symmetry transform
International Journal of Computer Vision - Special issue on qualitative vision
Junctions: Detection, Classification, and Reconstruction
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Robust Image Corner Detection Through Curvature Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sparse Pixel Vectorization: An Algorithm and Its Performance Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Identification of Fork Points on the Skeletons of Handwritten Chinese Characters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection of line junctions and line terminations using curvilinear features
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Improving the Accuracy of Skeleton-Based Vectorization
GREC '01 Selected Papers from the Fourth International Workshop on Graphics Recognition Algorithms and Applications
A Local Algorithm for Real-Time Junction Detection in Contour Images
CAIP '01 Proceedings of the 9th International Conference on Computer Analysis of Images and Patterns
Integrated Edge and Junction Detection with the Boundary Tensor
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Detection and characterization of junctions in a 2D image
Computer Vision and Image Understanding
Behavior of the Laplacian of Gaussian Extrema
Journal of Mathematical Imaging and Vision
Robust and Accurate Vectorization of Line Drawings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local invariant feature detectors: a survey
Foundations and Trends® in Computer Graphics and Vision
International Journal on Document Analysis and Recognition
Performance evaluation of corner detectors using consistency and accuracy measures
Computer Vision and Image Understanding
Dominant point detection: A new proposal
Image and Vision Computing
IEEE Transactions on Image Processing
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In this paper, we present a new approach for junction detection and characterization in line-drawing images. We formulate this problem as searching for optimal meeting points of median lines. In this context, the main contribution of the proposed approach is three-fold. First, a new algorithm for the determination of the support region is presented using the linear least squares technique, making it robust to digitization effects. Second, an efficient algorithm is proposed to detect and conceptually remove all distorted zones, retaining reliable line segments only. These line segments are then locally characterized to form a local structure representation of each crossing zone. Finally, a novel optimization algorithm is presented to reconstruct the junctions. Junction characterization is then simply derived. The proposed approach is very highly robust to common geometry transformations and can resist a satisfactory level of noise/degradation. Furthermore, it works very efficiently in terms of time complexity and requires no prior knowledge of the document content. Extensive evaluations have been performed to validate the proposed approach using other baseline methods. An application of symbol spotting is also provided, demonstrating quite good results.