Face Recognition based Texture Analysis Methods | Zendy

Marwa Y. Mohammed | Zendy

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Face Recognition based Texture Analysis Methods

Author(s) -

Marwa Y. Mohammed

Publication year - 2019

Publication title -

international journal of image graphics and signal processing

Language(s) - English

Resource type - Journals

eISSN - 2074-9082

pISSN - 2074-9074

DOI - 10.5815/ijigsp.2019.07.01

Subject(s) - biometrics , euclidean distance , artificial intelligence , local binary patterns , pattern recognition (psychology) , computer science , principal component analysis , facial recognition system , computer vision , face (sociological concept) , gray level , image (mathematics) , histogram , social science , sociology

A unimodal biometric system based Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) is developed to recognize the facial of 40 subjects. The matching process is implemented using three classifiers: Euclidean distance, Manhattan distance, and Cosine distance. The maximum accuracy (100%) is satisfied when GLCM and LBP are applied with Euclidean distance. The accuracy result of these two methods is advanced the Principle Component Analysis (PCA) and Fourier Descriptors (FDs) recognition rate. The ORL database is considered for constructing the proposed biometric system.

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