| 基于HRCenterNet模型改进的朝鲜语古籍文字检测方法 |
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| 引用本文： | 郭洪壮,金小峰.基于HRCenterNet模型改进的朝鲜语古籍文字检测方法[J].延边大学理工学报,2022,0(3):235-241. |
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| 作者姓名： | 郭洪壮 金小峰 |
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| 作者单位： | (延边大学 工学院, 吉林 延吉 133002) |
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| 摘 要： | 为减少朝鲜语古籍中的小文字错检和漏检问题,提出了一种基于HRCenterNet模型改进的朝鲜语古籍文字检测方法.首先,将HRCenterNet中Bottleneck模块的3×3卷积运算替换为Involution算子,即将Bottleneck模块替换为Involution - Bottleneck模块.其次,通过引入ECA(efficient channel attention)注意力机制扩展Involution - Bottleneck模块,并由此提出了基于IENeck模块的HRCenterNet改进模型.最后,利用朝鲜语古籍数据集对改进的HRCenterNet模型和原模型分别进行了训练,并测试了其在不同IOU下的准确率、召回率以及F1等指标.实验结果表明,在IOU ≥ 0.6时,改进的HRCenterNet模型在朝鲜语古籍数据集上的准确率、召回率和F1指标均优于原模型,且IOU值越高模型的检测效果越好.这表明改进的HRCenterNet模型显著优于原模型,可应用于朝鲜语古籍文字的检测中.
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| 关 键 词： | 古籍文字检测 朝鲜语古籍 Involution算子 ECA注意力机制 |
Korean ancient books character detection method based on improved HRCenterNet model |
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| GUO Hongzhuang,JIN Xiaofeng.Korean ancient books character detection method based on improved HRCenterNet model[J].Journal of Yanbian University (Natural Science),2022,0(3):235-241. |
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| Authors: | GUO Hongzhuang JIN Xiaofeng |
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| Affiliation: | (College of Engineering, Yanbian University, Yanji 133002, China) |
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| Abstract: | In order to reduce the misdetection and omission of small characters in Korean ancient books, an improved Korean ancient book character detection method based on HRCenterNet model was proposed.First, replace the 3×3 convolution operation of the Bottleneck module in HRCenterNet with the Involution operator, that is, replace the Bottleneck module with the Involution - Bottleneck module.Second, by introducing the efficient channel attention(ECA)mechanism to extend the Involution - Bottleneck module, an improved HRCenterNet model based on the IENeck module is proposed.Finally, the improved HRCenterNet model and the original model are trained separately using the Korean ancient book dataset, and the precision, recall, and F1 of different models under different IOUs are tested.The experimental results show that when IOU ≥ 0.6, the precision, recall and F1 index of the improved HRCenterNet model on the Korean ancient book data set are better than the original model, and the higher the IOU value, the better the detection effect of the model.This shows that the improved HRCenterNet model is significantly better than the original model, and can be applied to the detection of Korean ancient books. |
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| Keywords: | text detection of ancient books Korean ancient book Involution operator ECA mechanism |
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