Pattern Spectrum and Multiscale Shape Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Boundary Detection by Constrained Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Morphological Pattern Restoration from Noisy Binary Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constrained Restoration and the Recovery of Discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analysis and implementation of morphological skeleton transforms
Circuits, Systems, and Signal Processing - Special issue: median and morphological filters
Gibbs Random Fields, Cooccurrences, and Texture Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graphical Models and Image Processing
Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling
International Journal of Computer Vision
Size-biased random closed sets
ISMM '98 Proceedings of the fourth international symposium on Mathematical morphology and its applications to image and signal processing
Size distributions in stochastic geometry
Size distributions in stochastic geometry
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Spatial Size Distributions: Applications to Shape and Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Connectivity: Multiscale Analysis and Application to Generalized Granulometries
Journal of Mathematical Imaging and Vision
Statistical Characterization of Morphological Operator Sequences
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Object-Based Image Analysis Using Multiscale Connectivity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constrained texture synthesis for image post processing
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Optimal periodic memory allocation for image processing with multiple windows
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
An implementation of the vectorizing-based automatic nesting software NST
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part II
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A new class of Gibbs random fields (GRFs) is proposed capable of modeling geometrical constraints in images by means of mathematical morphology. The proposed models, known as morphologically constrained GRFs, model images by means of their size density. Since the size density is a multiresolution statistical summary, morphologically constrained GRFs explicitly incorporate multiresolution information into image modeling. Important properties are studied and their implication to texture synthesis and analysis is discussed. For morphologically constrained GRFs to be useful in practice, it is important that an efficient technique is available for fitting these models to real data. It is shown that, at low enough temperatures and under a natural condition, the maximum-likelihood estimator of the morphologically constrained GRF parameters can be approximated by means of an important tool of mathematical morphology known as the pattern spectrum. Therefore, statistical inference can be easily implemented by means of mathematical morphology. This allows the design of a computationally simple morphological Bayes classifier which produces excellent results in classifying natural textures.