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An Edge Detection Method using a Fuzzy Ensemble Approach

Journal
Acta Polytechnica Hungarica
ISSN
1785-8860
Date Issued
2017
Author(s)
Moya-Albor, Ernesto  
Facultad de Ingeniería - CampCM  
Ponce, Hiram  
Facultad de Ingeniería - CampCM  
Brieva, Jorge  
Facultad de Ingeniería - CampCM  
Type
text::journal::journal article
DOI
10.12700/APH.14.3.2017.3.9
URL
https://scripta.up.edu.mx/handle/20.500.12552/4419
Abstract
Edge detection is one of the most important low level steps in image processing. In this work we propose a fuzzy ensemble based method for edge detection including a fuzzy c-means (FCM) approach to define the input membership functions of the fuzzy inference system (FIS). We tested the performance of the method using a public database with ground truth. Also, we compared our proposal with classical and other fuzzy based methods, using F-measure curves and the precision metric. We conducted experiments with different levels of salt & pepper noise to evaluate the performance of the edge detectors. The metrics illustrate the robustness of the choice of the threshold in the binarization step using this fuzzy ensemble method. In noisy conditions, the proposed method works better than other fuzzy approaches. Comparative results validated that our proposal overcomes traditional techniques. © 2017, Budapest Tech Polytechnical Institution. All rights reserved.
Subjects

Edge detection

Fuzzy clustering

Fuzzy inference syste...

Image processing

Noise

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