<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Age estimation from face images is one of the significant topics in the field of machine vision, which is of great interest to controlling age access and targeted marketing. In this article, there are two main stages for human age estimation; the first stage consists of extracting features from the face areas by using Pseudo Zernike Moments (PZM), Active Appearance Model (AAM), and Bio-Inspired Features (BIF). In the second step, Support Vector Machine (SVM) and Support Vector Regression (SVR) algorithms are used to predict the age range of face images. The proposed method has been assessed utilizing the renowned databases of IMDB-WIKI and WIT-DB. In general, from all results obtained in the experiments, we have concluded that the proposed method can be chosen as the best method for Age estimation from face images.</p>
</abstract>

Age estimation from face images is one of the significant topics in the field of machine vision, which is of great interest to controlling age access and targeted marketing. In this article, there are two main stages for human age estimation; the first stage consists of extracting features from the face areas by using Pseudo Zernike Moments (PZM), Active Appearance Model (AAM), and Bio-Inspired Features (BIF). In the second step, Support Vector Machine (SVM) and Support Vector Regression (SVR) algorithms are used to predict the age range of face images. The proposed method has been assessed utilizing the renowned databases of IMDB-WIKI and WIT-DB. In general, from all results obtained in the experiments, we have concluded that the proposed method can be chosen as the best method for Age estimation from face images.

A New Hybrid Model to Predict Human Age Estimation from Face Images Based on Supervised Machine Learning Algorithms

Department of Electronic and Communication, Faculty of Engineering

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Age estimation from face images is one of the significant topics in the field of machine vision, which is of great interest to controlling age access and...

A New Hybrid Model to Predict Human Age Estimation from Face Images Based on Supervised Machine Learning Algorithms

Online veröffentlicht: 12. Juni 2023

Seitenbereich: 20 - 33

Eingereicht: 26. Jan. 2023

Akzeptiert: 12. Mai 2023

DOI: https://doi.org/10.2478/cait-2023-0011

Schlüsselwörter
Age estimation, Feature extraction, Feature selection, SVM, SVR

© 2023 Mohammed Jawad Al-Dujaili et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

A New Hybrid Model to Predict Human Age Estimation from Face Images Based on Supervised Machine Learning Algorithms

Online veröffentlicht: 12. Juni 2023

Seitenbereich: 20 - 33

Eingereicht: 26. Jan. 2023

Akzeptiert: 12. Mai 2023

DOI: https://doi.org/10.2478/cait-2023-0011

SchlüsselwörterAge estimation, Feature extraction, Feature selection, SVM, SVR

© 2023 Mohammed Jawad Al-Dujaili et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Age estimation, Feature extraction, Feature selection, SVM, SVR