The algebraic basis of mathematical morphology. I. dilations and erosions
Computer Vision, Graphics, and Image Processing
Three-dimensional alpha shapes
ACM Transactions on Graphics (TOG)
A New Way to Represent the Relative Position between Areal Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Pointshop 3D: an interactive system for point-based surface editing
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Analysis of the Spatial Arrangement of Cells in the Proliferative Breast Lesions
ICIAP '95 Proceedings of the 8th International Conference on Image Analysis and Processing
A Graph-Based Approach to the Structural Analysis of Proliferative Breast Lesions
AIME '95 Proceedings of the 5th Conference on Artificial Intelligence in Medicine in Europe: Artificial Intelligence Medicine
A survey of content-based image retrieval with high-level semantics
Pattern Recognition
Groups of Adjacent Contour Segments for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Morphological mesh filtering and α-objects
Pattern Recognition Letters
Multiscale Categorical Object Recognition Using Contour Fragments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph-based tools for microscopic cellular image segmentation
Pattern Recognition
Some Morphological Operators in Graph Spaces
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
Milena: Write Generic Morphological Algorithms Once, Run on Many Kinds of Images
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
Journal of Visual Communication and Image Representation
Computing with words with the ontological self-organizing map
IEEE Transactions on Fuzzy Systems - Special section on computing with words
Geometric Feature Extraction by a Multimarked Point Process
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Detection with Discriminatively Trained Part-Based Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discriminative Learning of Local Image Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatically finding clusters in normalized cuts
Pattern Recognition
Molecular dynamics-like data clustering approach
Pattern Recognition
Robust skeletonization using the discrete λ-medial axis
Pattern Recognition Letters
Improving vector space embedding of graphs through feature selection algorithms
Pattern Recognition
A general stochastic clustering method for automatic cluster discovery
Pattern Recognition
On the ternary spatial relation "Between"
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
Retraction and Generalized Extension of Computing With Words
IEEE Transactions on Fuzzy Systems
On the shape of a set of points in the plane
IEEE Transactions on Information Theory
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High-level spatial relation and configuration modeling issues are gaining momentum in the image analysis and pattern recognition fields. In particular, it is deemed important whenever one needs to mine high-content images or large scale image databases in a more expressive way than a purely statistically one. Continuing previous efforts to incorporate structural analysis by developing specific efficient morphological tools performing on mesh representations like Delaunay triangulations, we propose to formalize spatial relation modeling techniques dedicated to unorganized point sets. We provide an original mesh lattice framework which is more convenient for structural representations of large image data by means of interest point sets and their morphological analysis. The set of designed numerical operators is based on a specific dilation operator that makes it possible to handle concepts like ''between'' or ''left of'' over sparse representations of image data such as graphs. Based on this new theoretical framework for reasoning about images, we are able to process high-level queries over large histopathological images, knowing that digitized histopathology is a new challenge in the field of bio-imaging due to the high-content nature and large size of these images.