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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE)
Normakristagaluh, Pesigrihastamadya
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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A Brief Overview of Several Challenges in Finger Vascular Pattern Recognition Normakristagaluh, Pesigrihastamadya
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 6, No 1 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v6i1.22391

Abstract

Finger vascular pattern recognition biometrics are gaining popularity because they are hard to duplicate and more convenient. However, the challenges addressed during this research are not well-known to the public. Therefore, this paper presents an overview of challenges in finger vein pattern recognition. The challenges described arise from three possible things, namely imaging devices, finger physiology, and the surrounding environment. An illustrative experiment for one of the challenges has been carried out by producing that overexposure illumination during the image acquisition process can cause loss of vein pattern images. In addition, the experiment results on one of the finger images with different skin colors (light and dark) are shown in the histogram of the two images, where there is a slight difference in the graph pattern. From this paper, it is expected that the results of the illustrative experiments, as well as the general issues presented in this study, will inspire further research. Some of the work in this paper is part of the Ph.D thesis of Pesigrihastamadya Normakristagaluh.
Peningkatan Performa Pengenalan Wajah pada Gambar Low-Resolution Menggunakan Metode Super-Resolution Rohim, Muhammad Imaduddin Abdur; Nisa, Auliati; Hindratno, Muhammad Nurkhoiri; Fajri, Radhiyatul; Wibowanto, Gembong Satrio; Lestriandoko, Nova Hadi; Normakristagaluh, Pesigrihastamadya
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 1: Februari 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20241117947

Abstract

Kartu Tanda Penduduk Elektronik (KTP-el) merupakan identitas wajib bagi penduduk Indonesia. Penyimpanan pada cip KTP-el yang mana selain digunakan untuk menyimpan gambar potret wajah individu, juga harus dapat menyimpan identitas lain seperti biodata, tanda tangan, dan sidik jari kiri dan kanan. Keterbatasan tersebut mengharuskan gambar potret wajah disimpan pada ukuran low-resolution (LR) sehingga sistem pengenalan wajah tidak optimal. Dalam penelitian ini, kami menggunakan Poznan University of Technology (PUT) Face database yang terdiri atas 200 gambar dari 100 individu. Data tersebut dilakukan proses down sampling menggunakan bicubic interpolation untuk menghasilkan data LR. Kami menginvestigasi penggunaan metode super-resolution (SR) berbasis deep learning, termasuk DFDNet, LapSRN, GFPGAN, Real-ESRGAN, Real-ESRGAN+GFPGAN, dan FaceSPARNet. Hal ini bertujuan untuk meningkatkan kualitas gambar LR. Evaluasi performa dilakukan dengan menggunakan matriks False Rejection Rate(FRR) pada beberapa tingkatan False Acceptance Rate (FAR). Hasil penelitian menunjukkan bahwa beberapa metode SR terutama FaceSPARNet menunjukkan peningkatan performa face recognition hingga 2%. Sedangkan, metode SR yang berbasis GAN (GFPGAN, Real-ESRGAN, Real-ESRGAN+GFPGAN) cenderung meningkatkan false reject rate. Penelitian ini menunjukkan bahwa metode SR dari kategori General Basic CNN-based FSR dapat digunakan untuk meningkatkan kinerja face recognition pada gambar LR, seperti pada KTP-el.
Co-Authors Fajri, Radhiyatul Hindratno, Muhammad Nurkhoiri Nisa, Auliati Nova Hadi Lestriandoko Rohim, Muhammad Imaduddin Abdur Wibowanto, Gembong Satrio