Universiti Teknologi Malaysia Institutional Repository

Near infrared face recognition using Zernike moments and Hermite kernels

Farokhi, Sajad and Sheikh, Usman Ullah and Flusser, Jan and Yang, Bo (2015) Near infrared face recognition using Zernike moments and Hermite kernels. Information Sciences, 316 . pp. 234-245. ISSN 0020-0855

Full text not available from this repository.

Official URL: http://dx.doi.org/10.1016/j.ins.2015.04.030


This work proposes a novel face recognition method based on Zernike moments (ZMs) and Hermite kernels (HKs) to cope with variations in facial expression, changes in head pose and scale, occlusions due to wearing eyeglasses and the effects of time lapse. Near infrared images are used to tackle the impact of illumination changes on face recognition, and a combination of global and local features is utilized in the decision fusion step. In the global part, ZMs are used as a feature extractor and in the local part, the images are partitioned into multiple patches and filtered patch-wise with HKs. Finally, principal component analysis followed by linear discriminant analysis is applied to data vectors to generate salient features and decision fusion is applied on the feature vectors to properly combine both global and local features. Experimental results on CASIA NIR and PolyU NIR face databases clearly show that the proposed method achieves significantly higher face recognition accuracy compared with existing methods.

Item Type:Article
Uncontrolled Keywords:decision fusion, face recognition, hermite kernel, near infrared, zernike moments
Subjects:A General Works
ID Code:58631
Deposited By: Haliza Zainal
Deposited On:04 Dec 2016 12:07
Last Modified:29 Mar 2017 08:32

Repository Staff Only: item control page