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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
Muhammad Zulhaj Aliansyah
Universitas Pembangunan Nasional Veteran Jawa Timur
Computer Science & IT

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Identification of paleographic curvature using skeletonization and key point detection Fadhilatul Fitriyah; Dian Andriana; Muhammad Zulhaj Aliansyah; Lukman Hakim; Muhammad Faishol Amrulloh
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 2: April 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i2.27502

Abstract

Jawi script represents a vital component of the Islamic intellectual heritage of the Nusantara, preserved across numerous classical manuscripts. A primary challenge in digitizing these documents is character segmentation, particularly where handwritten characters connect without distinct boundaries. This research proposes a skeletonization-based segmentation method to address this issue, utilizing a dataset from 17 pages of the “Kitab Syair Perahu” manuscript containing 269 test characters. The pre-processing stage involves grayscale conversion, binarization, and noise removal through connected component analysis (CCA). The segmentation process then integrates skeleton structures, centroid positioning, intersection points, and loop detection. Evaluation results show the system successfully identified 187 out of 269 characters, achieving an accuracy of 0.801, a precision of 0.895, a recall of 86.38%, and an F1-score of 88.91%. While these results demonstrate the method’s effectiveness, the small dataset from a single manuscript limits its generalizability. Nevertheless, this study establishes a foundational step toward an automated Jawi image-processing system and the digital preservation of Islamic Nusantara literacy, contributing a tailored skeletonization-based approach for Jawi script.
Application of the traveling salesman problem to optimize skeletonization and stroke reconstruction Alifah Alifah; Dian Andriana; Muhammad Zulhaj Aliansyah; Lukman Hakim; Kholid Murtadlo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 24, No 2: April 2026
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v24i2.27504

Abstract

The preservation of Turots Nusantara manuscripts written in Pegon script faces significant challenges due to physical deterioration and the complexity of handwritten styles. This study proposes a novel digitization approach based on image processing to extract and reconstruct handwriting strokes by combining skeletonization and the travelling salesman problem (TSP) algorithm. The novelty of this research lies in the application of a modified Greedy TSP algorithm capable of recognizing branching and cyclic structures typical of Arabic–Pegon characters, enabling accurate reconstruction of handwritten stroke sequences. The process involves preprocessing (grayscale, thresholding, and morphological operations), skeleton extraction using a thinning method, and weighted graph construction based on Euclidean distance between skeleton points. The proposed system achieved an average precision of 0.552, recall of 0.815, F1-score of 0.657, and accuracy of 0.82. These results demonstrate the method’s effectiveness in detecting and reconstructing character shapes from Pegon manuscripts. Practically, this approach offers potential applications in the automatic digitization, preservation, and analysis of Pegon script, contributing to the conservation of Indonesia’s Islamic intellectual and cultural heritage.
Co-Authors Alifah Alifah Dian Andriana Fadhilatul Fitriyah Kholid Murtadlo Lukman Hakim Muhammad Faishol Amrulloh