Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/74437
Title: Fuzzy Logic Based Sclera Recognition
Authors: Das, Abhijit
Pal, Umapada
Ferrer Ballester, Miguel Ángel 
Blumenstein, Michael
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Biometrics
Sclera Vessels Patterns
D-LBP
SVM
Bag of Features
Issue Date: 2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Journal: IEEE International Fuzzy Systems conference proceedings 
Conference: IEEE International Conference on Fuzzy Systems 
Abstract: In this paper a sclera recognition and validation system is proposed. Here sclera segmentation was performed by Fuzzy logic-based clustering. Since the sclera 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/10553/74437
ISSN: 1544-5615
Source: 2014 IEEE International Conference on Fuzzy Systems (Fuzz-Ieee) [ISSN 1544-5615], p. 561-568, (2014)
Appears in Collections:Actas de congresos
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