WASET
	%0 Journal Article
	%A Fatima Akhmedova and  Simon Liao
	%D 2015
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 102, 2015
	%T Face Recognition Using Discrete Orthogonal Hahn Moments
	%U https://publications.waset.org/pdf/10002256
	%V 102
	%X One of the most critical decision points in the design of a
face recognition system is the choice of an appropriate face representation.
Effective feature descriptors are expected to convey sufficient, invariant
and non-redundant facial information. In this work we propose a set of
Hahn moments as a new approach for feature description. Hahn moments
have been widely used in image analysis due to their invariance, nonredundancy
and the ability to extract features either globally and locally.
To assess the applicability of Hahn moments to Face Recognition we
conduct two experiments on the Olivetti Research Laboratory (ORL)
database and University of Notre-Dame (UND) X1 biometric collection.
Fusion of the global features along with the features from local facial
regions are used as an input for the conventional k-NN classifier. The
method reaches an accuracy of 93% of correctly recognized subjects for
the ORL database and 94% for the UND database.
	%P 1543 - 1549