Spatially-Variant Anisotropic Morphological Filters Driven by Gradient Fields

Authors:
Rafael Verdú-Monedero;Jesús Angulo;Jean Serra
Affiliations:
Department of Information Technologies and Communications, Technical University of Cartagena, Cartagena, Spain 30202;CMM-Centre de Morphologie Mathématique, Mathématiques et Systèmes, MINES Paristech, Fontainebleau Cedex, France 77305;Laboratoire A2SI - ESIEE, B.P. 99, Noisy-le-Grand, France 93162
Venue:
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
Year:
2009

Citing 15
Cited 2

Analyzing oriented patterns

Computer Vision, Graphics, and Image Processing
The algebraic basis of mathematical morphology. I. dilations and erosions

Computer Vision, Graphics, and Image Processing
The algebraic basis of mathematical morphology

CVGIP: Image Understanding
Generalized gradient vector flow external forces for active contours

Signal Processing - Special issue on deformable models and techniques for image and signal processing
Directional Morphological Filtering

IEEE Transactions on Pattern Analysis and Machine Intelligence
Systematic Methods for the Computation of the Directional Fields and Singular Points of Fingerprints

IEEE Transactions on Pattern Analysis and Machine Intelligence
Morphological Image Analysis: Principles and Applications

Morphological Image Analysis: Principles and Applications
Path Openings and Closings

Journal of Mathematical Imaging and Vision
Image Analysis and Mathematical Morphology

Image Analysis and Mathematical Morphology
Locally adaptable mathematical morphology using distance transformations

Pattern Recognition
Image filtering using morphological amoebas

Image and Vision Computing
Theoretical Foundations of Spatially-Variant Mathematical Morphology Part II: Gray-Level Images

IEEE Transactions on Pattern Analysis and Machine Intelligence
Anisotropic Continuous-Scale Morphology

IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Grey-Scale Morphology with Spatially-Variant Rectangles in Linear Time

ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Orientation diffusions

IEEE Transactions on Image Processing

Morphological filtering on graphs

Computer Vision and Image Understanding
Adaptive morphology using tensor-based elliptical structuring elements

Pattern Recognition Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper deals with the theory and applications of spatially-variant mathematical morphology. We formalize the definition of spatially variant dilation/erosion and opening/closing for gray-level images using exclusively the structuring function, without resorting to complement. This sound theoretical framework allows to build morphological operators whose structuring elements can locally adapt their orientation across the dominant direction of image structures. The orientation at each pixel is extracted by means of a diffusion process of the average square gradient field, which regularizes and extends the orientation information from the edges of the objects to the homogeneous areas of the image. The proposed filters are used for enhancement of anisotropic images features such as coherent, flow-like structures.