TY - JOUR AU - Hameed Shaker, Shaimaa AU - Al-Khalidi , Farah Q. PY - 2022/05/24 Y2 - 2024/03/29 TI - Human Gender and Age Detection Based on Attributes of Face JF - International Journal of Interactive Mobile Technologies (iJIM) JA - Int. J. Interact. Mob. Technol. VL - 16 IS - 10 SE - Papers DO - 10.3991/ijim.v16i10.30051 UR - https://online-journals.org/index.php/i-jim/article/view/30051 SP - pp. 176-190 AB - <p>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. &nbsp;The results showed that the accuracy of the proposal was 90.93%,&nbsp; and F-measure was 89.4.</p> ER -