App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 9

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 Shaanxi 710055, China
2. Shaanxi Provincial Institute of Cultural Relics Protection, Xi'an Shaanxi 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. The proposed model, named MP-CNN, addresses this issue through a pose-aligned multi-part fine-grained recognition approach. In the first stage, a spatial transformer is employed to guide inscriptions to adopt a consistent glyph posture, aiding the model in accurately locating key text regions. The second stage involves 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, a feature fusion layer is built to obtain the recognition results. Experimental results demonstrate that the algorithm achieved 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 Accepted Paper, Vol. 41, 2024 No. 9

Publish History

[2024-02-23] Accepted Paper

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 (9). (2024-05-14). https://doi.org/10.19734/j.issn.1001-3695.2023.11.0594. (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 (9). (2024-05-14). https://doi.org/10.19734/j.issn.1001-3695.2023.11.0594. )

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  • Application Research of Computers Monthly Journal
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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.

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