TY - GEN
T1 - Image Enhancement and Thresholding for Ancient Inscriptions in Trowulan Museum's Collection Mojokerto, Indonesia
AU - Yuadi, Imam
AU - Halim, Yunus Abdul
AU - Asyhari, Agustian Taufiq
AU - Nisa, Khoirun
AU - Nazikhah, Nisak Ummi
AU - Nihaya, Ullin
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Inscriptions are an important source of information that supports archaeological and historical research. However, several significant challenges are due to surface damage, fading, and environmental wear, which often obscure the legibility of inscriptions and interfere with the identification process. This research aims to improve the readability of ancient inscriptions in the Trowulan Museum collection, in Mojokerto, Indonesia, by applying several image processing techniques. Grayscale and Contrast Limited Adaptive Histogram Equalization (CLAHE) methods are applied to improve image quality. Next, four types of thresholding methods including Niblack, Otsu, Sauvola, and Phansalkar were compared to produce the clearest image. Based on the results of calculating the mean, standard deviation, SNR, and PSNR, this research shows that the sauvola method produces brighter and clearer images with the least noise, but has the potential to lose writing identified as noise. On the other hand, the Phansalkar method, with a mean of 200.536, a standard deviation of 104.509, an SNR value of 1.585 dB, and a PSNR value of 6.188 dB, emerges as a viable alternative for preserving fine details in text that are often identified as noise by other methods.
AB - Inscriptions are an important source of information that supports archaeological and historical research. However, several significant challenges are due to surface damage, fading, and environmental wear, which often obscure the legibility of inscriptions and interfere with the identification process. This research aims to improve the readability of ancient inscriptions in the Trowulan Museum collection, in Mojokerto, Indonesia, by applying several image processing techniques. Grayscale and Contrast Limited Adaptive Histogram Equalization (CLAHE) methods are applied to improve image quality. Next, four types of thresholding methods including Niblack, Otsu, Sauvola, and Phansalkar were compared to produce the clearest image. Based on the results of calculating the mean, standard deviation, SNR, and PSNR, this research shows that the sauvola method produces brighter and clearer images with the least noise, but has the potential to lose writing identified as noise. On the other hand, the Phansalkar method, with a mean of 200.536, a standard deviation of 104.509, an SNR value of 1.585 dB, and a PSNR value of 6.188 dB, emerges as a viable alternative for preserving fine details in text that are often identified as noise by other methods.
KW - ancient inscriptions
KW - contrast limited adaptive histogram equalization
KW - cultural heritage
KW - image processing
KW - threshold
UR - http://www.scopus.com/inward/record.url?scp=85212710151&partnerID=8YFLogxK
U2 - 10.1109/IC2IE63342.2024.10747863
DO - 10.1109/IC2IE63342.2024.10747863
M3 - Conference contribution
AN - SCOPUS:85212710151
T3 - Proceedings 7th IC2IE 2024 - 2024 International Conference of Computer and Informatics Engineering: Generative AI in Democratizing Access to Knowledge and Skills
BT - Proceedings 7th IC2IE 2024 - 2024 International Conference of Computer and Informatics Engineering
A2 - Muharram, Asep Taufik
A2 - Rosalina, Mira
A2 - Kurniawati, Dewi
A2 - Yulianti, Susana Dwi
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference of Computer and Informatics Engineering, IC2IE 2024
Y2 - 12 September 2024 through 13 September 2024
ER -