Invoice Detection and Recognition System Based on Deep Learning

Xunfeng Yao, Hao Sun, Sijun Li, Wei Lu
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引用次数: 1

Abstract

With the development of economy and information technology, a large amount of invoice information has been produced. As one of the important components of the industrial Internet of Things, the recognition of invoice information is urgent to realize its intelligent recognition. Most invoice issuing units basically adopt traditional manual identification methods for the processing of invoices. As the number of invoices increases, problems such as low efficiency in identifying invoice information, error-prone, and difficulty in ensuring security frequently appear. In response to the above problems, this paper designs and implements an invoice information recognition system based on deep learning. The system first solves the problems of low image contrast and lack of image due to poor lighting or noise effects by image preprocessing methods such as image graying and normalization. Second, a target detection and invoice recognition method based on the combination of YOLOv3 + CRNN two models is proposed, and an end-to-end invoice information recognition model is obtained. Finally, the model is used to develop an invoice detection and recognition system based on deep learning. Experiments have verified that the system has the characteristics of high recognition accuracy and high efficiency, which can accurately identify invoice content information and reduce the loss of manpower and material resources.
基于深度学习的发票检测与识别系统
随着经济和信息技术的发展,产生了大量的发票信息。发票信息识别作为工业物联网的重要组成部分之一,迫切需要实现其智能识别。大多数发票开具单位基本采用传统的人工识别方式处理发票。随着发票数量的增加,发票信息识别效率低、易出错、安全性难以保证等问题频繁出现。针对上述问题,本文设计并实现了一个基于深度学习的发票信息识别系统。该系统首先通过图像灰度化、归一化等图像预处理方法,解决了由于光照或噪声影响导致的图像对比度低、图像缺失等问题。其次,提出了一种基于YOLOv3 + CRNN两种模型相结合的目标检测与发票识别方法,得到了端到端的发票信息识别模型;最后,利用该模型开发了一个基于深度学习的发票检测识别系统。实验证明,该系统具有识别精度高、效率高等特点,能够准确识别发票内容信息,减少人力物力的损失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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