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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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