Human Gender and Age Detection Based on Attributes of Face

Authors

  • Shaimaa Hameed Shaker Department of Computer sciences, University of Technology in Iraq, Baghdad
  • Farah Q. Al-Khalidi Department of Computer sciences, Mustansiriyah University in Iraq, Baghdad

DOI:

https://doi.org/10.3991/ijim.v16i10.30051

Keywords:

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

Abstract


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.

Cover iJIM Vol. 16 No. 10 (2022)

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Published

2022-05-24

How to Cite

Hameed Shaker, S. . ., & Al-Khalidi , F. Q. . (2022). Human Gender and Age Detection Based on Attributes of Face. International Journal of Interactive Mobile Technologies (iJIM), 16(10), pp. 176–190. https://doi.org/10.3991/ijim.v16i10.30051

Issue

Vol. 16 No. 10 (2022)

Section

Papers

License

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

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