Human Gender and Age Detection Based on Attributes of Face

Human Gender and Age Detection Based on Attributes of Face

Facial image, Features extraction, Human Age and Gender, k-mean, LDA, ID3.

The main target of the work in this paper is to detect the gender and oldness of a person with an accurate decision and efficient time based on the number of facial outward attributes extracted using Linear-Discriminate Analysis to classify a person within a certain category according to his(her) gender and age. This work was deal with color facial images via the Iterative Dichotomiser3 algorithm as a classifier to detect the oldness of a person after gender detected. This paper used the Face-Gesture-Recognition-Research-Network aging dataset. All facial images in the dataset were categorizing into binary categories using k-means. This is followed by the process of dividing all samples according to age classes that belonging to each specific sex category. Thus, this division process enabled us to reach a quick and accurate decision.  The results showed that the accuracy of the proposal was 90.93%,  and F-measure was 89.4.

Hameed Shaker, Shaimaa

Al-Khalidi , Farah Q.

International Journal of Interactive Mobile Technologies (iJIM); Vol. 16 No. 10 (2022); pp. 176-190

1865-7923

International Association of Online Engineering (IAOE), Vienna, Austria

2022-05-24

Copyright (c) 2022 Haider Th.Salim Alrikabi; Shaimaa Hameed Shaker, Farah Q. Al-Khalidi

https://creativecommons.org/licenses/by/4.0

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eng

info:eu-repo/semantics/article

info:eu-repo/semantics/publishedVersion

Peer-reviewed Article