New measures of homogeneity for image processing: an application to fingerprint segmentation

New measures of homogeneity for image processing: an application to fingerprint segmentation

In this work, we axiomatically describe the concepts of total homogeneity and local homogeneity of a fuzzy set. We also present different construction methods by means of restricted equivalence functions, restricted dissimilarity functions and implication operators. We show that the most common homo...

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Veröffentlicht in:Soft computing (Berlin, Germany) Germany), 2014-06, Vol.18 (6), p.1055-1066
Hauptverfasser: Jurio, A., Bustince, H., Pagola, M., Couto, P., Pedrycz, W.
Format: Artikel
Sprache:eng
Schlagworte:
Artificial Intelligence
Computational Intelligence
Control
Engineering
Fingerprints
Fuzzy sets
Homogeneity
Image processing
Image segmentation
Mathematical Logic and Foundations
Mechatronics
Methodologies and Application
Robotics
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Beschreibung
Zusammenfassung:In this work, we axiomatically describe the concepts of total homogeneity and local homogeneity of a fuzzy set. We also present different construction methods by means of restricted equivalence functions, restricted dissimilarity functions and implication operators. We show that the most common homogeneity expressions can be obtained as particular cases of the constructions developed here. The usefulness of these functions is shown in segmentation of fingerprint images.
ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-013-1126-3