Applied multivariate statistical analysis
Applied multivariate statistical analysis
Computer Vision, Graphics, and Image Processing
A critical view of pyramid segmentation algorithms
Pattern Recognition Letters
The adaptive pyramid: a framework for 2D image analysis
CVGIP: Image Understanding
Image segmentation from consensus information
Computer Vision and Image Understanding
Picture Segmentation by a Tree Traversal Algorithm
Journal of the ACM (JACM)
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
An Irregular Pyramid for Multi-scale Analysis of Objects and Their Parts
GbRPR '09 Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition
Advances in constrained connectivity
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
Evaluating minimum spanning tree based segmentation algorithms
CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
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A set of particular subgraphs of a valued graph, called cocoons, is introduced. Within the image segmentation framework, the cocoons represent a model of contrasted regions. It is shown that the cocoons are organized into a hierarchy which is a sub-hierarchy of the one produced by the standard clustering algorithm of complete linkage. This result thus offers a new point of view on what the complete linkage algorithm achieves when it is applied on image data. For segmentation purposes, the hierarchy is built on a region adjacency graph valued with a dissimilarity function. It's construction is efficient, parameter free, and robust towards monotone transformations of the dissimilarities. It is illustrated that the simplest cut criterion in these hierarchies, based on thresholding an associated ultrametric distance, already produces meaningful segmentations.