RECURSIVE LEARNING FUZZY LOGIC MODEL FOR BUILDING FEATURE EXTRACTOR IN IDENTIFICATION BIOMETRIC SYSTEM

Please use this identifier to cite or link to this item: https://dspace.univ-ouargla.dz/jspui/handle/123456789/17512

Title:	RECURSIVE LEARNING FUZZY LOGIC MODEL FOR BUILDING FEATURE EXTRACTOR IN IDENTIFICATION BIOMETRIC SYSTEM
Authors:	ASSAL, MEGHNIA MOULAY OMAR, MAHMOUD SMAHI, MOKHTAR
Keywords:	biometric system fuzzy logic learning palm modality feature vector
Issue Date:	2017
Abstract:	The objective of this dissertation is the integration of fuzzy logic to biometric systems for person identification. Fuzzy logic is used exactly to build the feature extractor of the biometric system. For this propose a fuzzy model for the image is chosen by selecting Gaussian membership functions for pixel coordinates and constants functions for gray level of pixels. The fuzzy model will be learned by an iterative procedure to extract the vector of characteristics. This biometric system is tested using Matlab software and a database of 500 persons with 12 images for each person. The results of simulation give good results with the FRR, FAR and EER values.
Description:	UNIVERSITY KASDI MERBAH OUARGLA Faculty of New Technologies of Information and Communication Department of Electronics and Communications
URI:	http://dspace.univ-ouargla.dz/jspui/handle/123456789/17512
Appears in Collections:	Département d'Electronique et des Télécommunications - Master

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