Image Segmentation of East OKU Script Using the Bounding Box Method for Cultural Heritage Digitization
DOI:
https://doi.org/10.35870/ijsecs.v5i2.4045Keywords:
OKU Timur Script, Bounding Box, Image Segmentation, Python, Google Colaboratory, DatasetAbstract
East Ogan Komering Ulu (OKU) is distinguished by its cultural heritage, which encompasses historical artifacts such as traditional houses, crafts, and ceremonial dances. Among the most significant cultural assets are relics inscribed with ancient scripts, including Pallawa and Ulu, which offer valuable insight into the region’s historical literacy. The present study addresses the segmentation of OKU Timur script images through the Bounding Box method. This approach was selected based on its practicality and efficiency, particularly in the context of datasets where script characters exhibit straightforward forms and the overall data volume remains manageable. The segmentation process utilizes Python within the Google Colaboratory platform, ensuring accessible and reproducible workflows. Accurate segmentation is essential to support ongoing digitization and preservation of cultural scripts. The methodology involves gathering data from local artifacts, converting images to binary format, and isolating characters using Bounding Boxes. The results demonstrate that the method effectively separates individual script characters, laying the groundwork for dataset development and subsequent image classification tasks.
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Copyright (c) 2025 M Fikri, Ilman Zuhri Yadi, Yesi Novaria Kunang, Leon Andretti Abdillah
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