A robust palmprint identification system using Histogram of Oriented Gradients and multi-classifiers

Abdallah Meraoumia, Salim Chitroub, Ahmed Bouridane

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Citations (Scopus)

Abstract

Nowadays, identification of persons has a great importance for information protection and access control. Thus, automatic person identification based on biometrics has become a focus of interest both for research and commercial purposes. Among the biometrics used, palmprint identification is one of the most stable and reliable technology. Some desirable properties such as uniqueness, stability, and non invasiveness make this technology suitable for highly reliable person identification. In this paper, a method is proposed based on Histogram of Oriented Gradients (HOG) descriptors for palmprint identification. This method utilized the fusion, at matching score level, of some classifiers (Radial Basis Function (RBF), Random Forest Transform (RTF) and Support Vector Machine (SVM)) to improve the performance in identification accuracy. Extensive experiments show the effectiveness of the proposed method with respect to the identification rate.
Original languageEnglish
Title of host publicationProceedings of the 2015 4th International Conference on Electrical Engineering (ICEE)
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1-4
ISBN (Print)9781467366731
DOIs
Publication statusPublished - 15 Dec 2015
Event4th International Conference on Electrical Engineering (ICEE 2015) - Boumerdés
Duration: 15 Dec 2015 → …

Conference

Conference4th International Conference on Electrical Engineering (ICEE 2015)
Period15/12/15 → …

Fingerprint Dive into the research topics of 'A robust palmprint identification system using Histogram of Oriented Gradients and multi-classifiers'. Together they form a unique fingerprint.

Cite this