A t-Norm Based Approach to Edge Detection

Authors:
C. Lopez-Molina;H. Bustince;J. Fernández;E. Barrenechea;P. Couto;B. Baets
Affiliations:
Departamento de Automática y Computación, Universidad Pública de Navarra, Pamplona, Spain;Departamento de Automática y Computación, Universidad Pública de Navarra, Pamplona, Spain;Departamento de Automática y Computación, Universidad Pública de Navarra, Pamplona, Spain;Departamento de Automática y Computación, Universidad Pública de Navarra, Pamplona, Spain;Department of Engineering, CITAB, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal 5001-801;Dept. of Applied Mathematics, Biometrics and Process Control, Universiteit Gent, Gent, Belgium 9000
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Year:
2009

Citing 10
Cited 0

A Computational Approach to Edge Detection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge detection by scale multiplication in wavelet domain

Pattern Recognition Letters
Edge detection in multispectral images using the self-organizing map

Pattern Recognition Letters
Automatic edge detection using 3 × 3 ideal binary pixel patterns and fuzzy-based edge thresholding

Pattern Recognition Letters
Scale-adaptive detection and local characterization of edges based on wavelet transform

Signal Processing - Signal processing in communications
A novel edge detection method based on the maximizing objective function

Pattern Recognition
A novel approach for edge detection based on the theory of universal gravity

Pattern Recognition
Interval-valued fuzzy sets constructed from matrices: Application to edge detection

Fuzzy Sets and Systems
Aggregation Functions: A Guide for Practitioners

Aggregation Functions: A Guide for Practitioners
A geometric approach to edge detection

IEEE Transactions on Fuzzy Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we study a modification of the original method by Genyun Sun et al. [1] for egde detection based on the Law of Universal Gravitation. We analyze the effect of the substitution of the product by other t-norms in the calculation of the gravitatory forces. We construct a fuzzy set where memberships to the edges are extracted from the magnitude of the resulting force on each pixel. To finish, we experimentally proof that the features of each t-norm determine the kind of edges to be detected.