Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46188
Title: Normalization and feature extraction on ear images
Authors: González, Esther 
Alvarez, Luis 
Mazorra, Luis 
UNESCO Clasification: 1203 Ciencia de los ordenadores
1206 Análisis numérico
2405 Biometría
Keywords: Ear Recognition
Normalization
Ear Images
Identification
Biometry, et al
Issue Date: 2012
Conference: 46th Annual IEEE International Carnahan Conference on Security Technology (ICCST) 
Abstract: Ear image analysis is an emerging biometrie application. A method for normalizing ear images and extracting from them a set of measurable features (feature vector) that can be used to identify its owner is proposed. The identification would be made based on the comparison between the feature vector of the input image and all feature vectors of the images in the database we work with. The feature vector is based on the ear contours. One important goal of this paper is to identify the most significant areas in the ear contour for human being identification purpose. Another important contribution of the paper is the combination of active contours techniques and ovoid model ear fitting (used to normalize ear features) and a high accurate invariant approach of internal and external ear contours. Ear geometry is characterized using a set of distances to external and internal contours points. This set of distances, along with six ovoid parameters is considered as the feature vector of the image. To test the method a new ear images database has been created. The proposed method identifies front-parallel views pretty good, even when varying the distance of the individual to the camera or the camera lens.
URI: http://hdl.handle.net/10553/46188
ISBN: 978-1-4673-2450-2
ISSN: 1071-6572
DOI: 10.1109/CCST.2012.6393543
Source: Proceedings - International Carnahan Conference on Security Technology [ISSN 1071-6572] (6393543), p. 97-104
Appears in Collections:Actas de congresos
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