Adaptive structuring elements based on salience information

Authors:
Vladimir Ćurić;Cris L. Luengo Hendriks
Affiliations:
Centre for Image Analysis, Uppsala University and Swedish University of Agricultural Sciences, Uppsala, Sweden;Centre for Image Analysis, Uppsala University and Swedish University of Agricultural Sciences, Uppsala, Sweden
Venue:
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
Year:
2012

Citing 15
Cited 0

A Computational Approach to Edge Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Distance transformations in digital images

Computer Vision, Graphics, and Image Processing
Salience distance transforms

Graphical Models and Image Processing
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
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
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
Edge-preserving smoothing using a similarity measure in adaptive geodesic neighbourhoods

Pattern Recognition
A simple method for detecting salient regions

Pattern Recognition
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
Morphological bilateral filtering and spatially-variant adaptive structuring functions

ISMM'11 Proceedings of the 10th international conference on Mathematical morphology and its applications to image and signal processing
Anisotropic Morphological Filters With Spatially-Variant Structuring Elements Based on Image-Dependent Gradient Fields

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Adaptive structuring elements modify their shape and size according to the image content and may outperform fixed structuring elements. Without any restrictions, they suffer from a high computational complexity, which is often higher than linear with respect to the number of pixels in the image. This paper introduces adaptive structuring elements that have predefined shape, but where the size is adjusted to the local image structures. The size of adaptive structuring elements is determined by the salience map that corresponds to the salience of the edges in the image, which can be computed in linear time. We illustrate the difference between the new adaptive structuring elements and morphological amoebas. As an example of its usefulness, we show how the new adaptive morphological operations can isolate the text in historical documents.