基于SWT算法的临床医学文献文本检测

Jingyi Wang, Zhao Liu
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引用次数: 0

摘要

临床医学文档图像中含有丰富的文本信息,文本区域的检测是后续文本分析的基础。然而,现有的文本检测算法主要针对单一语言,对于中英文混合文本的检测效果并不理想。为此,本文提出了一种基于笔画宽度变换(SWT)算法的中英文混合文本检测算法。该算法首先对图像进行预处理,然后确定连通域,并根据连通域的形态规则确定和过滤文本区域,然后根据笔画特征将像素连接成汉字和英文字符,最后输出图像的文本区域结果。仿真实验结果表明,该算法比传统的文本检测算法能更好地检测临床医学文档图像中的中英文混合文本区域,效果更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Text Detection of Clinical Medical Documents Based on SWT Algorithm
Clinical medical document images are rich in rich text information, and the detection of text areas is the basis for subsequent text analysis. However, the existing text detection algorithms are mainly for a single language, and the results for mixed Chinese and English text detection are not ideal. In this regard, this paper proposes a hybrid Chinese and English text detection algorithm based on the stroke width transform (SWT) algorithm. The algorithm first preprocesses the image, then determines the connected domain, and determines and filters the text area based on the morphological rules of the connected domain, then connects the pixels into Chinese characters and English characters according to the stroke characteristics, and finally outputs the text area result of the image. The simulation experiment results show that the algorithm can detect the Chinese and English mixed text areas in clinical medical document images better than the traditional text detection algorithm, and the effect is better.
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