Ear Print Recognition Based On Local Texture Descriptors.

Please use this identifier to cite or link to this item: https://dspace.univ-ouargla.dz/jspui/handle/123456789/21929

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DC Field	Value	Language
dc.contributor.author	CHACHA. Sabrina, CHACHA. Seida	-
dc.contributor.author	AIADI .Oussama	-
dc.date.accessioned	2019-11-11T07:50:16Z	-
dc.date.available	2019-11-11T07:50:16Z	-
dc.date.issued	2019-11-11	-
dc.identifier.uri	http://dspace.univ-ouargla.dz/jspui/handle/123456789/21929	-
dc.description.abstract	Ear recognition has attracted a lot of attention during the last decade. In this work, we develop a system for ear recognition based on local texture descriptors. In particular, we propose to employ Gray-Level Co-Occurrence Matrix (GLCM) and Local Binary Patterns descriptors for describing ear images. We conduct experiments on the well-known IIT-Delhi-I dataset which is made up of 493 images from 125 persons. Experimental results yield promising result.	en_US
dc.description.sponsorship	University of Kasdi Merbah, Ouargla Faculty of New Information and Communication Technologies Department of Computer Science and Information Technology	en_US
dc.language.iso	en	en_US
dc.subject	Ear Recognition , texture descriptors dataset	en_US
dc.title	Ear Print Recognition Based On Local Texture Descriptors.	en_US
Appears in Collections:	Département d'Electronique et des Télécommunications - Master

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