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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 10
3194-3200

Fine-grained recognition of untranscribed bronze inscriptions based on multi-category morphology

Liu Kexin1
Wang Huiqin1
Wang Ke1
Wang Zhan2
Wang Hong2
1. School of Information & Control Engineering, Xi'an Univversity of Architecture & Technology, Xi'an 710055, China
2. Shaanxi Provincial Institute of Cultural Relics Protection, Xi'an 710075, China
DOI: 10.19734/j.issn.1001-3695.2023.11.0594

Abstract

Fine-grained recognition of untranscribed bronze inscriptions relies on traditional convolutional neural networks. However, this method used overlooks the relationship between localization and feature learning, leading to difficulties in accurately representing the complex structures of the text and resulting in recognition errors. This paper proposed a model, named MP-CNN, addressed this issues through a pose-aligned multi-part fine-grained recognition approach. In the first stage, it employed a spatial transformer to guide inscriptions to adopt a consistent glyph posture, aiding the model in accurately locating key text regions. The second stage incorporated constructing a cascaded efficient channel attention(ECA) mechanism to guide the combination of feature channels, locating multiple independent discriminative regions and refining the extraction of morphological features for complex text structures. Finally, in the third stage, it built a feature fusion layer to obtain the recognition results. Experimental results demonstrate that the algorithm achieves recognition accuracies of 97.25% and 97.18% on standard and multi-category morphology datasets, respectively. Compared to the traditional convolutional network ResNet34, the method exhibits improvements of 4.63% and 8.89% on these datasets. The results indicate that the algorithm effectively adapts to the actual morphological variations in inscriptions, achieving fine-grained recognition of untranscribed bronze inscriptions.

Foundation Support

陕西省自然科学基础研究计划项目(2021JM-377)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.11.0594
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 10
Section: Technology of Graphic & Image
Pages: 3194-3200
Serial Number: 1001-3695(2024)10-045-3194-07

Publish History

[2024-02-23] Accepted Paper
[2024-10-05] Printed Article

Cite This Article

刘可欣, 王慧琴, 王可, 等. 多类别形态的未隶定青铜器铭文细粒度识别 [J]. 计算机应用研究, 2024, 41 (10): 3194-3200. (Liu Kexin, Wang Huiqin, Wang Ke, et al. Fine-grained recognition of untranscribed bronze inscriptions based on multi-category morphology [J]. Application Research of Computers, 2024, 41 (10): 3194-3200. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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