Computer Vision, Graphics, and Image Processing
Hierarchical Image Analysis Using Irregular Tessellations
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Median Graphs: Properties, Algorithms, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
A Syntactic Approach to Scale-Space-Based Corner Description
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical watersheds within the combinatorial pyramid framework
DGCI'05 Proceedings of the 12th international conference on Discrete Geometry for Computer Imagery
Directly computing the generators of image homology using graph pyramids
Image and Vision Computing
Assessing the role of spatial relations for the object recognition task
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Combinatorial pyramids and discrete geometry for energy-minimizing segmentation
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part II
A distance measure between labeled combinatorial maps
Computer Vision and Image Understanding
Hierarchical Correlation of Multi-Scale Spatial Pyramid for Similar Mammogram Retrieval
International Journal of Digital Library Systems
Multimedia Tools and Applications
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Irregular pyramids are made of a stack of successively reduced graphs embedded in the plane. Such pyramids are used within the segmentation framework to encode a hierarchy of partitions. The different graph models used within the irregular pyramid framework encode different types of relationships between regions. This paper compares different graph models used within the irregular pyramid framework according to a set of relationships between regions. We also define a new algorithm based on a pyramid of combinatorial maps which allows to determine if one region contains the other using only local calculus.