Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Teknika

Enhancing Image Quality in Facial Recognition Systems with GAN-Based Reconstruction Techniques Wijaya, Beni; Satyawan, Arief Suryadi; Haqiqi, Mokh. Mirza Etnisa; Susilawati, Helfy; Artemysia, Khaulyca Arva; Sopian, Sani Moch.; Shamie, M. Ikbal; Firman
Teknika Vol. 14 No. 1 (2025): March 2025
Publisher : Center for Research and Community Service, Institut Informatika Indonesia (IKADO) Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34148/teknika.v14i1.1180

Abstract

Facial recognition systems are pivotal in modern applications such as security, healthcare, and public services, where accurate identification is crucial. However, environmental factors, transmission errors, or deliberate obfuscations often degrade facial image quality, leading to misidentification and service disruptions. This study employs Generative Adversarial Networks (GANs) to address these challenges by reconstructing corrupted or occluded facial images with high fidelity. The proposed methodology integrates advanced GAN architectures, multi-scale feature extraction, and contextual loss functions to enhance reconstruction quality. Six experimental modifications to the GAN model were implemented, incorporating additional residual blocks, enhanced loss functions combining adversarial, perceptual, and reconstruction losses, and skip connections for improved spatial consistency. Extensive testing was conducted using Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) to quantify reconstruction quality, alongside face detection validation using SFace. The final model achieved an average PSNR of 26.93 and an average SSIM of 0.90, with confidence levels exceeding 0.55 in face detection tests, demonstrating its ability to preserve identity and structural integrity under challenging conditions, including occlusion and noise.  The results highlight that advanced GAN-based methods effectively restore degraded facial images, ensuring accurate face detection and robust identity preservation. This research provides a significant contribution to facial image processing, offering practical solutions for applications requiring high-quality image reconstruction and reliable facial recognition.
Co-Authors Ade Rukmana Ade Rukmana Adhitya Yusuf Wibysono Adiatma, Dani Aeni, Dinda Noorfaidah Afina Carmelya, Anindya Ahmad Noor Jaman ahmad rizal Akhmad Fauzi Ikhsan Akhmad Fauzi Ikhsan Alfaz Arva Baihaqi Aloysius Adya Pramudita Artemysia, Khaulyca Arva Baihaqi, Alfaz Arva Dani Prasetyo Adi, Puput Dhiky Juansyah Dinda Noorfaidah Aeni Dini Fajriani Etnisa, Moch Mirza Evi Novitasari Fadillah, Ardi Fajriani, Dini Fauzi, Moch Zulfi Fazri, Nurul Firman Firman Firman Fitri Nuraeni Galura Muhammad Suranegara Ghofur, Shaefan Afuan Ginaldi Ari Nugroho Gusman, Dilla Oktaviani Hamdani, Nizar Alam Haqiqi, Mokh. Mirza Etnisa Iik Muhammad Malik Matin Iik Muhammad Malik Matin Ikhsan, Akhmad Fauzi Jaman, Ahmad Noor Juansyah, Dhiky Juniawan, Ega Rizki Khoerunnisa, Ica Latukolan, Merlyn Inova Christie Lubis, Anggi Muhammad M.Angdarun, M.Angdarun Malikmatin, Iik Muhammad Matin, Iik Muhammad Malik Mirza Etnisa Haqiqi, Mokhamamad Muhamad, Reza Muhammad Ihsan Mutmainah, Rina Nasrullah Armi Novitasari, Evi Nurdin, Agung Ihwan Nurfalah, Rifki Nurfitriani, Nabila Nurichsan, Irman Reza Muhamad Rifki Nurfalah Rina Mutmainah RR. Ella Evrita Hestiandari Rukmana, Ade Samie, Muhammad Ikbal Satyawan, Arief Suryadi Sediono, Wahju Setyawan, Arief Suryadi Shaefan Afuan Ghofur Shamie, M. Ikbal Sifa Nurpadillah Sobari, Acep Hasan Sopian, Sani Moch Sopian, Sani Moch. Sri Nuraeni, Sri Sugandi, Gandi Sunardi, Dede Suryadi Satyawan, Arief Syarif Saeful Yusup Tri Arif Wiharso TRI ARIF WIHARSO Wibysono, Adhitya Yusuf Wiharso, Tri Arif Wiwik Handayani Yusup, Syarif Saeful