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All Journal Jurnal Kendali Teknik dan Sains Mars: Jurnal Teknik Mesin, Industri, Elektro dan Ilmu Komputer
Salsa Nabila Iskandar
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Computer Science & IT

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Penerapan Teknologi Pengolahan Citra dalam Analisis Data Visual pada Tinjauan Komprehensif Supiyandi Supiyandi; Muhammad Abdul Mujib; Khairul Azis; Rahmat Abdillah; Salsa Nabila Iskandar
Jurnal Kendali Teknik dan Sains Vol. 2 No. 3 (2024): Juli : Jurnal Kendali Teknik dan Sains
Publisher : Universitas Katolik Widya Karya Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jkts-widyakarya.v2i3.3796

Abstract

Image processing has become a key technology in visual data analysis, making significant contributions across various fields such as healthcare, security, and the creative industry. This article provides a comprehensive review of the application of image processing technology in visual data analysis, focusing on the latest methods, tools, and practical applications. We discuss various image processing techniques, including segmentation, edge detection, and pattern recognition, as well as how these techniques are applied to process and analyze visual data. The study also includes performance evaluations of various commonly used image processing algorithms and software. Additionally, we explore the challenges faced in applying this technology, such as image resolution issues, noise, and high computational demands. By offering an extensive overview of the development and implementation of image processing technology, this article aims to be a valuable reference for researchers and practitioners working in the field of visual data analysis.
Deteksi Wajah dalam Foto Menggunakan Teknologi Visi Komputer Supiyandi Supiyandi; Tegar Ardiansyah; Sri Putri Balqis; Jundi Haqqoni; Salsa Nabila Iskandar
Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer Vol. 2 No. 6 (2024): Desember : Mars : Jurnal Teknik Mesin, Industri, Elektro Dan Ilmu Komputer
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/mars.v2i6.490

Abstract

This study discusses the implementation of computer vision technology for face detection in photos using two sample images with variations in lighting and face pose. The developed system combines the Viola-Jones algorithm and Convolutional Neural Networks (CNN) to enhance resilience against lighting and face orientation variations. Experimental results show high accuracy even with only two sample images. This research also develops preprocessing techniques to handle extreme lighting conditions and demonstrates efficient implementation using Python and OpenCV.
Co-Authors Jundi Haqqoni Khairul Azis Muhammad Abdul Mujib Rahmat Abdillah Sri Putri Balqis Supiyandi Supiyandi Tegar Ardiansyah