首页> 外文会议>International Conference on speech and computer >Generation of Synthetic Images of Full-Text Documents
【24h】

Generation of Synthetic Images of Full-Text Documents

机译:全文文档合成图像的生成

获取原文

摘要

In this paper, we present an algorithm for generating images of full-text documents. Such images can be used to train and evaluate models of optical character recognition. The algorithm is modular, individual parts can be changed and tweaked to generate desired images. We describe a method for obtaining background images of paper from already digitalized documents. We use a Variational Autoencoder to train a generative model of these backgrounds enabling the generation of similar background images as the training ones on the fly. The module for printing the text uses large text corpora, font, and suitable positional and brightness noise to obtain believable results. We use Tesseract OCR to compare the real world and generated images and observe that the recognition rate is very similar indicating the proper appearance of the synthetic images. Furthermore, the mistakes made by the OCR system in both cases are alike. Finally, the system generates detailed, structured annotation of the synthesized image.
机译:在本文中,我们提出了一种用于生成全文本文档图像的算法。此类图像可用于训练和评估光学字符识别模型。该算法是模块化的,可以更改和调整各个部分以生成所需的图像。我们描述了一种从已经数字化的文档中获取纸张背景图像的方法。我们使用变分自动编码器来训练这些背景的生成模型,从而能够实时生成与训练背景相似的背景图像。用于打印文本的模块使用较大的文本语料库,字体以及适当的位置噪声和亮度噪声来获得可信的结果。我们使用Tesseract OCR比较现实世界和生成的图像,并观察到识别率非常相似,表明合成图像的正确外观。此外,OCR系统在两种情况下所犯的错误都是相似的。最后,系统生成合成图像的详细的结构化注释。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号