Performance analysis of Gabor 2D PCA feature extraction for gender identification using face

Automatic gender recognition using face of person is vital topic for research and having practical applications in crime investigation and prohibited entry in specific gender restricted area. Key Research issue of gender recognition is improving the accuracy of system which is measured in term of recognition rate and Feature Extraction process is key factor for accuracy of system. Face has unique edge pattern (shape) and texture for male and female. In this paper, Gabor filter is used to extract the pattern of edges from face image but it generate huge dimension with high level redundant features which is reduced by proposed two level feature reduction techniques.