Age Identification Through Facial Images Using Gabor Filter and Convolutional Neural Network (CNN)

Authors

  • Zahra Nabila Izdihar Computer Science Department, BINUS Graduate Program, Bina Nusantara University – 11480, Jakarta, Indonesia
  • Simeon Yuda Prasetyo Computer Science Department, BINUS Graduate Program, Bina Nusantara University – 11480, Jakarta, Indonesia
  • Samuel Philip Computer Science Department, BINUS Graduate Program, Bina Nusantara University – 11480, Jakarta, Indonesia
  • Sani Muhamad Isa Computer Science Department, School of Computer Science, Bina Nusantara University – 11480, Jakarta, Indonesia

Keywords:

Age estimation, Computer Vision, CNN, Deep Learning, Face Recognition, Gabor filter

Abstract

Age prediction plays a very important role in helping prevent document falsification, identity fraud, age theft cases or other crimes. This research uses CNN to predict age, because CNN has a better performance in facial recognition. Then, the researcher also changed the filter in CNN using a Gabor filter to extract facial features to predict age. The Gabor filter method is often used in texture analysis because it is effective in recognizing patterns. Therefore, the Gabor filter method is known as a successful feature detector because it has the ability to eliminate facial variability. This research uses 8 types of experiments (CNN model only or a combination of CNN and Gabor filters) by comparing 4 types of CNN architecture, namely Standard CNN, VGG16, VGG19 and ResNet50. The best accuracy results are obtained from the VGG19 model which has an MAE value of 5.8235 with an execution time of 15 minutes 24 seconds. While the lowest computation time is obtained from the VGG16+Gabor model which is 7 minutes 4 seconds. Of the eight experiments that have been carried out, the Gabor filter has the advantage that it always has a lower computation time so that the Gabor filter is proven to be more efficient in predicting the age.

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References

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Published

17.02.2023

How to Cite

[1]
Z. . Nabila Izdihar, S. . Yuda Prasetyo, S. . Philip, and S. . Muhamad Isa, “Age Identification Through Facial Images Using Gabor Filter and Convolutional Neural Network (CNN)”, Int J Intell Syst Appl Eng, vol. 11, no. 2, pp. 164–169, Feb. 2023.

Issue

Vol. 11 No. 2 (2023): (Article in Press)

Section

Research Article

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