Abstract
Null space linear discriminant analysis (NLDA) and linear discriminant analysis based on generalized singular value decomposition (LDA/GSVD) are two popular linear discriminant analysis (LDA) methods that can solve Small Sample Size (SSS) problem. In this paper we present the relation between NLDA and LDA/GSVD under a mild condition, and propose a modified NLDA (MNLDA) algorithm. By both theoretical analysis and experimental results on ORL and FERET face databases, the proposed MNLDA has been proved to have the same discriminating power as LDA/GSVD and to be more efficient than LDA/GSVD.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
