An Oracle Bone Inscriptions Detection Algorithm Based on Improved YOLOv8

Author:

Zhen Qianqian12,Wu Liang12,Liu Guoying12

Affiliation:

1. School of Software Engineering, Anyang Normal University, Anyang 455000, China

2. Henan Province Oracle Bone Culture Intelligent Industry Engineering Research Center, Anyang 455000, China

Abstract

Ancient Chinese characters known as oracle bone inscriptions (OBIs) were inscribed on turtle shells and animal bones, and they boast a rich history dating back over 3600 years. The detection of OBIs is one of the most basic tasks in OBI research. The current research aimed to determine the precise location of OBIs with rubbing images. Given the low clarity, severe noise, and cracks in oracle bone inscriptions, the mainstream networks within the realm of deep learning possess low detection accuracy on the OBI detection dataset. To address this issue, this study analyzed the significant research progress in oracle bone script detection both domestically and internationally. Then, based on the YOLOv8 algorithm, according to the characteristics of OBI rubbing images, the algorithm was improved accordingly. The proposed algorithm added a small target detection head, modified the loss function, and embedded a CBAM. The results show that the improved model achieves an F-measure of 84.3%, surpassing the baseline model by approximately 1.8%.

Funder

Special Project for Cultural Research of Henan Xing Culture Engineering

National Natural Science Foundation—Henan Province Joint Fund

China Association of Higher Education

Anyang City Science and Technology Research Project

Publisher

MDPI AG

Reference26 articles.

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5. Xiaosong, S., Yongjie, H., and Yongge, L. (2016, January 3–5). Text on Oracle rubbing segmentation method based on connected domain. Proceedings of the 2016 IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC), Xi’an, China.

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