Face recognition using kernel entropy component analysis

✍ Scribed by B.H. Shekar; M. Sharmila Kumari; Leonid M. Mestetskiy; Natalia F. Dyshkant

• Publisher: Elsevier Science
• Year: 2011
• Tongue: English
• Weight: 638 KB
• Volume: 74
• Category: Article
• ISSN: 0925-2312
• DOI: 10.1016/j.neucom.2010.10.012

✦ Synopsis

In this letter, we have reported a new face recognition algorithm based on Renyi entropy component analysis. In the proposed model, kernel-based methodology is integrated with entropy analysis to choose the best principal component vectors that are subsequently used for pattern projection to a lowerdimensional space. Extensive experimentation on Yale and UMIST face database has been conducted to reveal the performance of the entropy based principal component analysis method and comparative analysis is made with the kernel principal component analysis method to signify the importance of selection of principal component vectors based on entropy information rather based only on magnitude of eigenvalues.