EXPLANATION OF FEATURE EXTRACTION IN FACE RECOGNITION USING VIOLA JONES ALGORITHM

Face recognition has become a common thing used in the field of surveillance and security in computer technology and image devices. This study aims to identify the usefulness of a person's face on 3 test images. This study examines the methods of cropping techniques, image enhancement through intensity measurement, and histogram analysis to improve the contrast and distribution of image intensity. In addition, the Viola-Jones algorithm is used to detect key facial features such as eyes, nose, and mouth. The results of the analysis are then applied in the feature evaluation stage, where usually between facial features are applied to measure the ratio of facial proportions. Furthermore, the comparison of proportional ratios of several images was analyzed using bar graphs and line graphs to evaluate the trend and stability of facial proportions. The results showed the best ratio stability with a smaller variation of the on-off ratio of image 2 which is 0.4762 pixels to 0.4983 pixels. Image 2 is the most ideal for face measurement systems based on geometric ratios because it provides more consistent and visible results.

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Publication Details

Journal
JURTEKSI (Jurnal Teknologi dan Sistem Informasi)
Published
2025-06-29
DOI
https://doi.org/10.33330/jurteksi.v11i3.3844
Primary Topic
Face and Expression Recognition
Type
article
Field-Weighted Citation Impact
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article

EXPLANATION OF FEATURE EXTRACTION IN FACE RECOGNITION USING VIOLA JONES ALGORITHM

Eva Rianti, Retno Devita, Ondra Eka Putra, Muhammad Habib Yuhandri
JURTEKSI (Jurnal Teknologi dan Sistem Informasi)
Face and Expression Recognition
article

EXPLANATION OF FEATURE EXTRACTION IN FACE RECOGNITION USING VIOLA JONES ALGORITHM

Eva Rianti, Retno Devita, Ondra Eka Putra, Muhammad Habib Yuhandri
article en

Abstract

Face recognition has become a common thing used in the field of surveillance and security in computer technology and image devices. This study aims to identify the usefulness of a person's face on 3 test images. This study examines the methods of cropping techniques, image enhancement through intensity measurement, and histogram analysis to improve the contrast and distribution of image intensity. In addition, the Viola-Jones algorithm is used to detect key facial features such as eyes, nose, and mouth. The results of the analysis are then applied in the feature evaluation stage, where usually between facial features are applied to measure the ratio of facial proportions. Furthermore, the comparison of proportional ratios of several images was analyzed using bar graphs and line graphs to evaluate the trend and stability of facial proportions. The results showed the best ratio stability with a smaller variation of the on-off ratio of image 2 which is 0.4762 pixels to 0.4983 pixels. Image 2 is the most ideal for face measurement systems based on geometric ratios because it provides more consistent and visible results.

JURTEKSI (Jurnal Teknologi dan Sistem Informasi)Vol. 11(3)
Universitas Putra Indonesia "YPTK" (ID)
Openalex Percentile: Top 76%
Face and Expression Recognition
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