Article Per Year (5 Year)
p-Index From 2021 - 2026
0.983
P-Index
This Author published in this journals
All Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Nasional Komputasi dan Teknologi Informasi Journal of Artificial Intelligence and Digital Business Journal of Sustainable Innovation Engineering
Takyudin, Takyudin
Unknown Affiliation
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Neuroscience Transportation

Published : 5 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal of Sustainable Innovation Engineering

 1 
Innovative Edge Detection Approaches for Arabic Character Recognition in Kitab Kuning Images: A Comparison of Sobel, Prewitt, and Canny takyudin, takyudin
Journal of Sustainable Innovation Engineering Vol. 1 No. 3 (2025): November
Publisher : Institute Of Advanced Knowledge and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/sustainable.v1i3.20

Abstract

The preservation of Kitab Kuning manuscripts as part of Islamic intellectual heritage requires digitalization and image enhancement to ensure readability and sustainability. One of the essential stages in digital manuscript processing is edge detection, which plays an important role in extracting the structural shape of Arabic characters. This study aims to compare the performance of three classical edge detection methods—Sobel, Prewitt, and Canny—in detecting the edges of Arabic characters in Kitab Kuning manuscript images. Each manuscript image was preprocessed through grayscale conversion and Gaussian filtering before applying the three edge detection algorithms. The resulting edge images were evaluated using Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Structural Similarity Index (SSIM). The experimental results show that the Canny method consistently produces lower MSE values, higher PSNR, and more stable SSIM compared to Sobel and Prewitt, resulting in clearer, smoother, and more accurate edge structures resembling the original Arabic characters. Prewitt demonstrates moderate performance, while Sobel tends to generate rougher edges and is more sensitive to noise. Based on these findings, the Canny method is recommended as the most effective approach for Arabic character edge detection in the digital preservation of Kitab Kuning manuscripts, supporting better quality enhancement and long-term usability of digital Islamic manuscripts
Co-Authors Aland Polma Naek Sihombing Hamsar , Ali Hamsar, Ali Iskandar Fitri, Iskandar Putra , Jonni Adi Putra, Jonni Adi Rais , Muhammad Sandi Selvanda, Alifia Restu Sihombing, Aland Polma Naek Yuhandri Yuhandri, Yuhandri