论文标题
关于财务票证图像的全宗教文本识别方法的研究
Research on All-content Text Recognition Method for Financial Ticket Image
论文作者
论文摘要
随着经济发展，财务票的数量迅速增加。传统的手动发票报销和财务会计系统为财务会计师带来了越来越多的负担。因此，基于对大量实际财务票证数据的研究和分析，我们设计了基于深度学习的所有内容的准确而有效的所有内容。此方法具有更高的认可准确性和召回率，并且可以满足财务会计工作的实际要求。此外，我们提出了一个财务票务角色识别框架（FTCRF）。根据汉字识别的特征，该框架包含一种两步信息提取方法，可以提高汉字识别的速度。实验结果表明，该方法的平均识别精度为91.75 \％，整个票为87 \％。该方法的可用性和有效性由商业应用系统验证，这大大提高了财务会计系统的效率。
With the development of the economy, the number of financial tickets increases rapidly. The traditional manual invoice reimbursement and financial accounting system bring more and more burden to financial accountants. Therefore, based on the research and analysis of a large number of real financial ticket data, we designed an accurate and efficient all contents text detection and recognition method based on deep learning. This method has higher recognition accuracy and recall rate and can meet the actual requirements of financial accounting work. In addition, we propose a Financial Ticket Character Recognition Framework (FTCRF). According to the characteristics of Chinese character recognition, this framework contains a two-step information extraction method, which can improve the speed of Chinese character recognition. The experimental results show that the average recognition accuracy of this method is 91.75\% for character sequence and 87\% for the whole ticket. The availability and effectiveness of this method are verified by a commercial application system, which significantly improves the efficiency of the financial accounting system.
