Wavelet, Gabor Filters and Co-occurrence Matrix for Palmprint Verification | Zendy

Anouar Ben Khalifa | Zendy; Lamia Rzouga | Zendy; Najoua Essoukri BenAmara | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Wavelet, Gabor Filters and Co-occurrence Matrix for Palmprint Verification

Author(s) -

Anouar Ben Khalifa,

Lamia Rzouga,

Najoua Essoukri BenAmara

Publication year - 2013

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.2013.08.01

Subject(s) - gabor wavelet , co occurrence matrix , artificial intelligence , pattern recognition (psychology) , computer science , computer vision , wavelet , biometrics , matrix (chemical analysis) , mathematics , wavelet transform , discrete wavelet transform , materials science , image processing , image (mathematics) , image texture , composite material

Authentication through the palmprint is a field of biometrics. Palmprint-based personal verification has quickly entered the biometric family. It has become increasingly popular in the recent years due to its ease of acquisition, reliability and high user acceptance. In this paper, we present an authentication system based on the palmprint. We are particularly interested in the feature extraction step. Three feature extraction techniques based on the discrete wavelet transform, the Gabor filters and the co-occurrence matrix are evaluated. The support vector machine is used for the classification step. The results have been validated on the PolyU database related to 400 users. The best results have been achieved with the wavelet decomposition

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research