Education, Science, Technology, Innovation and Life
Open Access
Sign In

Research on automatic segmentation and recognition of original topographic single characters based on intelligent recognition of oracle bones

Download as PDF

DOI: 10.23977/jeis.2024.090313 | Downloads: 8 | Views: 109

Author(s)

Bingbing Hou 1

Affiliation(s)

1 School of Mathematics and Statistics, Guangxi Normal University, Guilin, China

Corresponding Author

Bingbing Hou

ABSTRACT

The study of oracle bones is of great significance to the understanding of the development of Chinese and foreign civilizations, with the development of artificial intelligence computing, the text recognition of oracle bones has a more efficient method, and the use of machine vision related technology to achieve the text segmentation and text recognition of oracle bone topography can effectively improve the efficiency of the study of oracle bones. In this paper, the establishment of a series of models from the pre-processing of oracle bone topographies, the segmentation of oracle bone text to oracle bone text recognition is investigated. In this paper, we first preprocess the image of oracle bone topographies to eliminate the elements other than topographies, such as numbers and letters in the numbering, etc., and then use commonly used machine vision techniques to filter the image to reduce the impact of interference factors on oracle bone recognition, use image enhancement and image binarization techniques to make the text elements in the image more prominent, and finally use edge extraction techniques to extract the edge information of the text in the topographies.

KEYWORDS

Machine Vision, Image Preprocessing, K-Means, Yolov

CITE THIS PAPER

Bingbing Hou, Research on automatic segmentation and recognition of original topographic single characters based on intelligent recognition of oracle bones. Journal of Electronics and Information Science (2024) Vol. 9: 83-90. DOI: http://dx.doi.org/10.23977/10.23977/jeis.2024.090313.

REFERENCES

[1] Liu Guoying. Deep Learning Based Oracle Character Detection and Recognition [A]. Yindu Journal , 2020, 9(41):55-58.
[2] Men Yi, Zhang Shuangshang. Artificial Intelligence-based Oracle Recognition Technology and Glyph Database Construction[J]. Institute of Chinese Characters, 2021, 1(33):10-14.
[3]  Luo Ying, Zhang Yifeng, Jiang Jiansheng. Preprocessing Technology for Ray Detection of Negative Defect Images [A].Nondestructive testing, 2024, 2(46):23-27.
[4] Qian Wenjun, Wang Jixin, Du Haoran, Zhang Xunan .Gaussian Filtering of Drill Mast X-Ray Images Based on Various Improved Methods[A]. Laser journal, 2024:2-9.
[5] Ma Pan, Yang Ziheng, Wan Hu, He Shun, Huang Yuan, Xu Shengyong .Cotton Aphid Image Recognition Algorithm and Software System Design Based on YOLOv8 Network. [A]. Journal of intelligent agricultural equipment (Chinese and English), 2023, 3(4):43-46. 
[6] Yan Tao, Hu Xiaoping, Peng Qianqian, Huang Hong. Fusion of MSR and Improved CLAHE for Ampoule Image Enhancement[A].Automation and instrumentation, 2024, 5(39):85-88.
[7] Xiang Ling, Deng Xiaohua. Adaptive Evolutionary Model for Binarization of Multiplicative Noisy Text Images[A].Journal of Neijiang Normal University, 2023, 8(38):42-45.
[8] Shaomin Xie, Xinrong Li. Fast detection algorithm for small targets with weak edges in sub-pixel digital images [A]. Modern Electronic Technoiogy, 2024, 13(47):24-26.
[9] Yao F. Q., Zhang X. H., Zhang S., Zhai B.. Experimental analysis of edge detection algorithms for product size images of toothed roll crusher[A].Tianjin Science and Technology, 2024, 6(51):20-21.
[10] Zhenjie Li, Chunhua Zang, Baoyu Su, Xianggui Chen. Design of Image Processing Software Based on OpenCV[A]. Internet of Things, 2024, 6(12):47-49.

Downloads: 9649
Visits: 321989

Sponsors, Associates, and Links


All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.