Facial gender recognition using Gabor-DCT feature extraction

Abstract

Facial Gender Identification has vast application in human computer interaction, determines customer profile in shopping centers, and restricted permission to enter in prohibited zone, criminal profile analysis. This paper presents a robust process for illumination invariant compact feature extraction using Gabor filter for the automatic recognition for facial gender identification system. Face has uniqueness in edges and texture pattern for different gender category. Gabor filter can extract edge and textural patterns of faces but generate problem of huge dimensions and redundancy feature coefficients. In order to enhance the efficiency and accuracy of the system, this problem of enormous redundancy as well as dimension can be solved by proposing a new feature namely average-DCT feature reduction technique. Proposed Gabor-DCT has precise, accurate and compact feature pattern as well as early throughput for facial gender identification compared to other state of art method of Gabor filter.

Subject Classification:

• (2010) 68M12

Keywords:

• Facial gender recognition
• Gabor filter
• DCT