Human Gender and Age Detection Based on Attributes of Face
Keywords: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.
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Copyright (c) 2022 Haider Th.Salim Alrikabi; Shaimaa Hameed Shaker, Farah Q. Al-Khalidi
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