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http://hdl.handle.net/10553/46951
Title: | Sclera recognition using dense-SIFT | Authors: | Das, Abhijit Pal, Umapada Ballester, Miguel Angel Ferrer Blumenstein, Michael |
UNESCO Clasification: | Investigación | Keywords: | Biometric Sclera Vessel Patterns D-Sift Svm Bag Of Features, et al |
Issue Date: | 2014 | Journal: | International Conference on Intelligent Systems Design and Applications | Conference: | 2013 13th International Conference on Intellient Systems Design and Applications, ISDA 2013 | Abstract: | In this paper we propose a biometric sclera recognition and validation system. Here the sclera segmentation is performed bya time-adaptive active contour-based region growing technique. The sclera vessels are not prominent so image enhancement is required and hence a bank of 2D decomposition. A Haar wavelet multi-resolution filter is used to enhance the vessels pattern for better accuracy. For feature extraction, Dense Scale Invariant Feature Transform (D-SIFT) is used. D-SIFT patch descriptors of each training image are used to form bag of features by using k-means clustering and a spatial pyramid model, 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. Anencouraging Equal Error Rate (EER) of 0.66% is attained in the experiments presented. | URI: | http://hdl.handle.net/10553/46951 | ISBN: | 978-1-4799-3516-1 | ISSN: | 2164-7143 | DOI: | 10.1109/ISDA.2013.6920711 | Source: | International Conference on Intelligent Systems Design and Applications, ISDA [ISSN 2164-7143] (6920711), p. 74-79, (2013) |
Appears in Collections: | Actas de congresos |
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