Title:	Occlusion detection and index-based ear recognition
Authors:	Sultana, Madeena Polash Paul, Padma Gavrilova, Marina
Citation:	Journal of WSCG. 2015, vol. 23, no. 1, p. 121-129.
Issue Date:	2015
Publisher:	Václav Skala - UNION Agency
Document type:	článek article
URI:	http://wscg.zcu.cz/WSCG2015/!_2015_Journal_WSCG-No-2.pdf http://hdl.handle.net/11025/17155
ISSN:	1213–6972 (hardcopy) 1213–6980 (CD-ROM) 1213–6964 (online)
Keywords:	biometrické obrazy;detekce okluze;sluchové rozpoznávání;částečná okluze;klasifikace třídníku;výběr adaptivní funkce
Keywords in different language:	biometric images;occlusion detection;ear recognition;partial occlusion;classifier selection;adaptive feature selection
Abstract in different language:	Person recognition using ear biometric has received significant interest in recent years due to its highly discriminative nature, permanence over time, non-intrusiveness, and easy acquisition process. However, in a realworld scenario, ear image is often partially or fully occluded by hair, earrings, headphones, scarf, and other objects. Moreover, such occlusions may occur during identification process resulting in a dramatic decline of the recognition performance. Therefore, a reliable ear recognition system should be equipped with an automated detection of the presence of occlusions in order to avoid miss-classifications. In this paper, we proposed an efficient ear recognition approach, which is capable of detecting the presence of occlusions and recognizing partial ear samples by adaptively selecting appropriate features indices. The proposed method has been evaluated on a large publicly available database containing wide variations of real occlusions. The experimental results confirm that the prior detection of occlusion and the novel selection procedure for feature indices significantly improve the biometric system recognition accuracy.
Rights:	© Václav Skala - UNION Agency
Appears in Collections:	Volume 23, Number 2 (2015)

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