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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Journal of Information System
Moch. Arief Soeleman
Universitas Dian Nuswantoro
Computer Science & IT

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Analisa Deteksi Citra Kerusakan pada Body Mobil dengan Menggunakan Metode Deteksi Tepi Canny Dannya Deczi Nasdal; Moch. Arief Soeleman; A. Zainul Fanani
JOINS (Journal of Information System) Vol 9 No 1 (2024): Edisi Mei 2024
Publisher : Fakultas Ilmu Komputer, Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/joins.v9i1.10550

Abstract

Kendala dalam penggunaan bahan perbaikan body mobil sering kali muncul akibat analisis kerusakan yang tidak tepat yang hanya berdasarkan pengamatan mata. Kendala ini juga menjadi hambatan bagi perusahaan asuransi kendaraan dalam menentukan klaim yang sepadan dengan tingkat kerusakan. Untuk itu, peneliti mengajukan metode baru dalam menganalisis kerusakan body mobil dengan menggunakan segmentasi citra deteksi tepi canny berbasis algoritma Canny. Metode ini mampu mengidentifikasi garis tepi pada gambar kerusakan body mobil dan mengkalkulasi persentase piksel tepi yang menunjukkan tingkat kerusakan. Selain itu, penelitian ini juga mengaplikasikan noise filtering dengan algoritma Machine Learning untuk meningkatkan kualitas gambar sebelum proses segmentasi. Implementasi metode ini dilakukan dengan menggunakan software MatLab versi 2015a.
Optimation of image encryption using fractal Tromino and polynomial Chebyshev based on chaotic matrix Elkaf Rahmawan Pramudya; Moch. Arief Soeleman; Cahaya Jatmoko; Eko Hari Rachmawanto; Aris Marjuni; Pulung Nurtantio Andono; Folasade Olubusola Isinkaye
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 22, No 6: December 2024
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v22i6.26080

Abstract

Image encryption is a critical process aimed at securing digital images, safeguarding them from unauthorized access, tampering, or viewing to ensure the confidentiality and integrity of sensitive visual information. In this research, we integrate polynomial Chebyshev, fractal Tromino, and substitution S-box methods into a comprehensive image encryption approach. Our evaluation focuses on standardized 256×256-pixel images of Lena, Peppers, and Baboon, assessing key performance metrics like mean squared error (MSE), peak signal-to-noise ratio (PSNR), unified average changing intensity (UACI), number of pixel changes rate (NPCR), and entropy. The results reveal varying encryption quality across images, with Lena exhibiting the highest MSE (4702) and the lowest PSNR (12.89 dB). However, UACI, NPCR, and entropy values remain consistent across all images, indicating the proposed method’s stability concerning changing intensity, pixel alterations, and entropy levels. These findings contribute valuable insights into the effectiveness of the proposed encryption method, providing a foundation for further exploration and optimization in the field of cryptographic research. For future research direction, it is recommended to explore the impact of varying image sizes and types on the proposed method’s performance. Additionally, by focusing on the area of cryptographic threats, further analysis of the algorithm’s resistance against advanced attacks and its computational efficiency would be beneficial.
Co-Authors A. Zainul Fanani Aris Marjuni Cahaya Jatmoko Dannya Deczi Nasdal Eko Hari Rachmawanto Elkaf Rahmawan Pramudya Folasade Olubusola Isinkaye Pulung Nurtantio Andono