Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46950
Title: Fuzzy logic based selera recognition
Authors: Das, Abhijit
Pal, Umapada
Ballester, Miguel Angel Ferrer 
Blumenstein, Michael
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Iris recognition
Image segmentation
Feature extraction
biometrics (access control)
fuzzy logic
support vector machines
image classification
Issue Date: 2014
Journal: IEEE International Conference on Fuzzy Systems 
Conference: 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014 
Abstract: In this paper a selera recognition and validation system is proposed. Here selera segmentation was performed by Fuzzy logic-based clustering. Since the selera vessels are not prominent, image enhancement was required. A Fuzzy logic-based Brightness Preserving Dynamic Fuzzy Histogram Equalization and discrete Meyer wavelet was used to enhance the vessel patterns. For feature extraction, the Dense Local Binary Pattern (D-LBP) was used. D-LBP patch descriptors of each training image are used to form a bag of features, which is used to produce the training model. Support Vector Machines (SVMs) are used for classification. The UBIRIS version 1 dataset is used here for experimentation. An encouraging Equal Error Rate (EER) of 4.31% was achieved in our experiments.
URI: http://hdl.handle.net/10553/46950
ISBN: 9781479920723
ISSN: 1098-7584
DOI: 10.1109/FUZZ-IEEE.2014.6891684
Source: IEEE International Conference on Fuzzy Systems[ISSN 1098-7584] (6891684), p. 561-568
Appears in Collections:Actas de congresos
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