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Surya, Ibnu
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Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Social Sciences Other

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Analysis of Illumination Invariant Method for Face Detection in Different Lighting Variations Ivan Chatisa; Siti Syahidatul Helma; Ibnu Surya
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.12731

Abstract

Lighting quality is a crucial factor that affects the performance of camera-based face detection systems, especially in CCTV surveillance systems that operate in low or uneven lighting conditions. This study aims to analyze the performance of illumination-invariant preprocessing methods in improving the accuracy of human face detection under various lighting conditions. Three preprocessing approaches were compared, namely Histogram Equalization (HE), Gamma Correction (GC), and a hybrid method that combines both (GC+HE). The dataset used consists of 1415 human face images taken using a webcam with variations in five lighting conditions, four face directions, and three shooting distances. All images were processed using the Haar Cascade Classifier algorithm as the face detection method. Performance evaluation was conducted using accuracy, precision, recall, and confusion matrix analysis metrics. The test results showed that the hybrid method provided the best performance with a precision of 92.79%, accuracy of 87.49%, and recall of 89.61%, compared to the HE and GC methods used individually. This improvement indicates that the combination of lighting normalization and contrast enhancement can produce more stable and informative facial images for the detection process. The findings of this study indicate that the hybrid-based illumination invariant approach is very effective for application in real-time visual surveillance systems, especially in environments with limited lighting.
Co-Authors Adin Saf, Maksum Ro'is Agus Urip Ari Wibowo Ananda Ananda Ananda Tri Putra Anggy Trisnadoli Dewi, Tria Rosana Dhiemas Aditya Oktara Disa Putri, Tiara Ayu Dwi Putra, Nanda Fadhly Rida, Muhammad Arif Fani, Ridho Hawali Gebriani Amanda Putri Harumin Harumin Intan Sandra Yatana Saputri Irgi Yoga Pangestu Irma Wardani Ivan Chatisa Jan Alif Kreshna Juni Nurma Sari Kartina Diah K. W. Keken Melfasoni Khairul Umam Syaliman Maksum Rois Adin Saf Mardhiah Fadhli, Mardhiah Muhammad Ihsan Zul Panjaitan, Yoel Puja Hanifah Purnamasari, Devi Rahmat Suhatman Rika Perdana Sari, Rika Perdana Robert Robert Sapriadi, Sapriadi Satria Perdana Arifin Shelly Angella Silvana Rasio Henim Siti Syahidatul Helma Solikah, Umi Nur Suffanda, Zeri Suhatman, Rahmat Suwardi Tasya, Raudatul Thesa Nabila Balqis Pardede Weslie Weslie Yoanda Alim Syahbana Yoshandi, Tengku Mohammad Yuli Fitrisia Zainal Arifin Renaldo