Computationally Intelligent Gender Classification Techniques: An Analytical Study

Classification has emerged as a leading technique for problem solution and optimization. Classification has been used extensively in several problems domain. Automated gender classification is a significant area of research and has great potential. It offers several industrial applications in near future such as monitoring, surveillance, commercial profiling and human computer interaction. Different methods have been proposed for gender classification like gait, iris and hand shape. However, majority of techniques for gender classification are based on facial information. In this paper, a comparative study of gender classification using different techniques is presented. The major emphasis of this work is on the critical evaluation of different techniques used for gender classification. The comparative evaluation has highlighted major strengths and limitations of these existing techniques. Taking an overview of these major problems, our research is focused on summarizing the literature by highlighting its strengths and limitations. This study also presents several future research areas in the domain of gender classification.