Publication Type : Conference Paper
Publisher : Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on, IEEE,
Source : Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on, IEEE, Coimbatore (2009)
Url : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5393713
ISBN : 9781424450534
Accession Number : 11134380
Campus : Amritapuri
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2009
Abstract : The data in face images are distributed in a complex manner due to the variation of light intensity, facial expression and pose. In this paper the Kernel Principal Component Analysis (KPCA) is used to extract the feature set of male and female faces. A Gaussian model of skin segmentation method is applied here to exclude the global features such as beard, eyebrow, moustache, etc. both training and test images are randomly selected from four different data bases to improve the training. The experimental results show that the proposed framework is efficient for recognizing the gender of a face image even though it is an impersonation face.
Cite this Research Publication : S. Aji, Jayanthi, T., and Dr. Kaimal, M. R., “Gender Identification in Face Images using KPCA”, in Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on, Coimbatore, 2009