Survey on Human Gender Classification Using Biometric Information

One of the greatest vital and significant areas of research is the classification of gender. Gender classification is necessary and crucial for numerous commercial applications, including human-computer communication and computer-aided physiological or psychological analysis, because it comprises a varied range of information about the differences between male and female characteristics. To comprehensively assess gender classification research, this paper presents a survey of the available soft techniques for gender identification from biometric techniques, including biological information-based methods (biometric and bio-signal), and Non-Biological based methods (static and dynamic features). Iris recognition systems have drawn much interest among authentication methods because of their rich iris texture, which provides reliable standards for identifying people. However, most iris biometrics expertise and research have focused on identifying specific people. Therefore, this research can be seen as the first step in a more extensive investigation into iris recognition.