Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/46950
| Título: | Fuzzy logic based selera recognition | Autores/as: | Das, Abhijit Pal, Umapada Ballester, Miguel Angel Ferrer Blumenstein, Michael |
Clasificación UNESCO: | 3307 Tecnología electrónica | Palabras clave: | Iris recognition Image segmentation Feature extraction biometrics (access control) fuzzy logic, et al. |
Fecha de publicación: | 2014 | Editor/a: | Institute of Electrical and Electronics Engineers (IEEE) | Publicación seriada: | IEEE International Fuzzy Systems conference proceedings | Conferencia: | IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2014) | Resumen: | 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: | 1544-5615 | DOI: | 10.1109/FUZZ-IEEE.2014.6891684 | Fuente: | 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) [ISSN 1544-5615], p. 561-568 |
| Colección: | Actas de congresos |
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