基于OPENCV的电子教科书数字化

Zhi-Ming Deng, Minyong Shi, Chunfang Li
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引用次数: 2

摘要

传统的电子教科书数字化方法受文本数据和插图排版的限制,数据处理效果较差。为了适应复杂多变的数据格式,提出了一种自适应数据分区技术。我们将教科书中的所有文本和插图划分为独立的数据块,对其进行定位和切割,并使用OCR技术对每个区域的信息进行识别,使处理目标更加明确。在初中历史教科书上进行了数据识别率的实验。实验结果表明,本文提出的方法对电子教科书的数字化具有良好的效果。
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Digitalization of Electronic Textbook Based on OPENCV
The traditional digitization method of electronic textbooks is limited by text data and illustration layout, and the data processing effect is poor. In order to adapt to the complex and changeable data formats, this paper proposes an adaptive data partitioning technique. We divide all the texts and illustrations in the textbooks into independent data blocks, locate and cut them, and use OCR technology to identify the information of each area to make the processing goals more clear. Experiments were conducted on the junior middle school history textbooks in terms of data recognition rate. The experimental results show that the method proposed in this paper has a good effect on the digitalization of electronic textbooks.
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