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Biometric Authentication for Gender Classification Techniques: A Review

Publication Type : Journal Article

Publisher : Springer

Source : Journal of The Institution of Engineers (India): Series B, 99(1), 79-85

Url :

Campus : Chennai

School : School of Computing

Year : 2018

Abstract : One of the challenging biometric authentication applications is gender identification and age classification, which captures gait from far distance and analyze physical information of the subject such as gender, race and emotional state of the subject. It is found that most of the gender identification techniques have focused only with frontal pose of different human subject, image size and type of database used in the process. The study also classifies different feature extraction process such as, Principal Component Analysis (PCA) and Local Directional Pattern (LDP) that are used to extract the authentication features of a person. This paper aims to analyze different gender classification techniques that help in evaluating strength and weakness of existing gender identification algorithm. Therefore, it helps in developing a novel gender classification algorithm with less computation cost and more accuracy. In this paper, an overview and classification of different gender identification techniques are first presented and it is compared with other existing human identification system by means of their performance.

Cite this Research Publication : Mathivanan, P., &Poornima, K, "Biometric Authentication for Gender Classification Techniques: A Review", Journal of The Institution of Engineers (India): Series B 99(1), 79-85

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