Improvement Research and Application of Text Recognition Algorithm Based on CRNN

Lei Chen, Shaobin Li
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引用次数: 5

Abstract

This paper is based on CRNN model to recognize the text in the images of football matches scene, and two improvements are proposed. Considering the edge feature of text is strong, this paper adds MFM layers into CRNN model aiming to enhance the contrast. In order to solve the problem of losing details of image static features in the process of getting contextual features, this paper fuses up these two kinds of features. The training and testing experiments carried out on public dataset and manual dataset respectively verify the validity of the improvements, and the recognition accurate rate is higher than original model.
基于CRNN的文本识别算法改进研究与应用
本文基于CRNN模型对足球比赛场景图像中的文本进行识别,并提出了两种改进方法。考虑到文本的边缘特征较强,本文在CRNN模型中加入MFM层以增强对比度。为了解决图像静态特征在获取上下文特征过程中丢失细节的问题,本文将这两种特征融合在一起。在公共数据集和人工数据集上分别进行了训练和测试实验,验证了改进的有效性,识别准确率高于原始模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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