International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 85 - Number 7 |
Year of Publication: 2014 |
Authors: Swathi Kalam, Geetha Guttikonda |
10.5120/14855-3222 |
Swathi Kalam, Geetha Guttikonda . Gender Classification using Geometric Facial Features. International Journal of Computer Applications. 85, 7 ( January 2014), 32-37. DOI=10.5120/14855-3222
Gender classification has become an essential task in human computer interaction (HCI). Gender classification is used in immense number of applications like passive surveillance, control in smart buildings (restricting access to certain areas based on gender) and supermarkets, gender advertising, security investigation. So far detection of gender using facial features is done by using the methods like Gabor wavelets, artificial neural networks and support vector machine. In this work, facial distance measure is used as a progenitor to achieve the gender classification. The proposed approach performs gender classification using mathematical operations on the frontal pose face images using Matlab. This work can be further evaluated in future by using different databases with various poses other than the frontal pose.