基于模板与内容分离的发票识别方法

R. Shi, Sanxin Jiang
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引用次数: 0

摘要

从发票中提取和保存结构化信息是一项必要的任务。现有的方法都是为了检测和识别重复发票。该方法考虑到同类型发票之间存在大量重复内容和固定的表结构,提出采用像素分割的方法对发票的模板内容和填充内容进行分离;采用感知哈希算法将待测发票模板与模板数据库中的发票进行匹配;匹配成功后,使用改进的模板对齐模块将新填写的内容与模板发票对齐,然后将新发票导入Excel中保存。实验结果表明,与原方法相比,该方法的文本检测时间、识别时间和预测时间分别缩短了68%、91.13%和89.94%,整体预测时间缩短了27.26秒。
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Invoice Recognition Method Based on Separation of Template and Content
It is a necessary task to extract and save structured information from invoices. The existing methods are all to detect and identify the duplication of invoices. Considering that there are a lot of duplicate contents and fixed table structure between invoices of the same type, this method proposes to separate the template and filled contents of invoices by pixel segmentation; The perceptual hash algorithm is used to match the template of the invoice to be tested with the invoice in the template database; After successful matching, use the improved template alignment module to align the new filled content with the template invoice, and then import the new invoice into Excel for saving. Experimental results show that compared with the original method, the text detection time, recognition time and prediction time of this method are reduced by 68%, 91.13% and 89.94% respectively, and the overall prediction time is reduced by 27.26 seconds.
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