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Research on Automatic Segmentation and Recognition of Single Characters of Original Topography in Intelligent Recognition of Oracle Bone Inscriptions

  • Minghang Lv
  • , Siqi Bo
  • , Fuli Li*
  • , Pengjie Wu
  • , Zicheng Xiong
  • *Corresponding author for this work
  • Harbin Institute of Technology
  • Dalian University of Technology
  • School of Mathematics, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Intelligent recognition technology, as an important technical tool, has played a significant role in many fields. In this paper, for the issue of oracle bone image processing, we first conducted image pre-processing, including size adjustment, normalization, and data enhancement steps, to improve image quality and highlight the oracle bone information. Then, the YOLOv5 model is utilized for oracle bone image segmentation, achieving high recognition accuracy after 50 epochs of training. Finally, the model was employed to automatically segment the original oracle bone topography images for individual characters, with an average processing time of only 810.8ms, demonstrating efficient processing speed. In total, 1447 oracle bones were automatically detected and segmented, achieving a high level of accuracy.

Original languageEnglish
Title of host publicationInternational Conference on Advanced Image Processing Technology, AIPT 2024
EditorsLu Leng, Zhenghao Shi
PublisherSPIE
ISBN (Electronic)9781510682542
DOIs
StatePublished - 2024
Externally publishedYes
Event2024 International Conference on Advanced Image Processing Technology, AIPT 2024 - Chongqing, China
Duration: 31 May 20242 Jun 2024

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume13257
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference2024 International Conference on Advanced Image Processing Technology, AIPT 2024
Country/TerritoryChina
CityChongqing
Period31/05/242/06/24

Keywords

  • Intelligent recognition technology
  • YOLOv5
  • image processing
  • utomatically segment

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