Digital topology: introduction and survey
Computer Vision, Graphics, and Image Processing
Connectivity on Complete Lattices
Journal of Mathematical Imaging and Vision
Connected filtering and segmentation using component trees
Computer Vision and Image Understanding
Shape Preserving Filament Enhancement Filtering
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
A multiscale approach to connectivity
Computer Vision and Image Understanding
Object-Based Image Analysis Using Multiscale Connectivity
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mask-Based Second-Generation Connectivity and Attribute Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constrained Connectivity for Hierarchical Image Decomposition and Simplification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation of Complex Images Based on Component-Trees: Methodological Tools
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
Automatic Attribute Threshold Selection for Blood Vessel Enhancement
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Interactive segmentation based on component-trees
Pattern Recognition
Building the Component Tree in Quasi-Linear Time
IEEE Transactions on Image Processing
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This article introduces the notion of component-hypertree, which models the component-trees of an image at various connectivity levels, and the relations of the nodes/connected components between these levels. This data structure is then used to extend a recently proposed interactive segmentation method based on component-trees. In this multiscale connectivity context, the use of a component-hypertree appears to be less costly than the use of several component-trees. Application examples illustrate the relevance of this approach.