Adaptive morphology using tensor-based elliptical structuring elements

Authors:
Anders Landström;Matthew J. Thurley
Affiliations:
-;-
Venue:
Pattern Recognition Letters
Year:
2013

Citing 17
Cited 0

Mathematical morphology for structure without translation symmetry

Signal Processing
Viscous Lattices

Journal of Mathematical Imaging and Vision
Adaptive mathematical morphology for edge linking

Information Sciences—Informatics and Computer Science: An International Journal
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
Numerical residues

Image and Vision Computing
Theoretical Foundations of Spatially-Variant Mathematical Morphology Part I: Binary Images

IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Spatially-Variant Directional Mathematical Morphology Operators Based on a Diffused Average Squared Gradient Field

ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
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
Spatially-Variant Anisotropic Morphological Filters Driven by Gradient Fields

ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
Overview of adaptive morphology: trends and perspectives

ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Adaptivity and group invariance in mathematical morphology

ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Direction-adaptive grey-level morphology. application to 3D vascular brain imaging

ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Anisotropic Morphological Filters With Spatially-Variant Structuring Elements Based on Image-Dependent Gradient Fields

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.10

Visualization

Abstract

Mathematical Morphology is a common strategy for non-linear filtering of image data. In its traditional form the filters used, known as structuring elements, have constant shape once set. Such rigid structuring elements are excellent for detecting patterns of a specific shape, but risk destroying valuable information in the data as they do not adapt in any way to its structure. We present a novel method for adaptive morphological filtering where the local structure tensor, a well-known method for estimation of structure within image data, is used to construct adaptive elliptical structuring elements which vary from pixel to pixel depending on the local image structure. More specifically, their shape varies from lines in regions of strong single-directional characteristics to disks at locations where the data has no prevalent direction.