自动发票数据提取使用图像处理

Q2 Decision Sciences
A. A. Manjunath, Manjunath Sudhakar Nayak, Santhanam Nishith, Satish Nitin Pandit, Shreyas Sunkad, Pratiba Deenadhayalan, Shobha Gangadhara
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引用次数: 0

摘要

手工处理扫描复印件形式的发票是一个耗时的过程。需要以类似的格式自动执行从发票中提取数据的任务。在本文中,我们研究和分析了各种图像处理和文本提取技术,以改善光学字符识别(OCR)引擎的结果,该引擎用于从发票中提取文本。本文还提出了一个基于web的发票处理系统(IPS)的设计与实现。IPS由标注工具和抽取工具组成。注释工具用于标记要提取的发票中感兴趣的字段。提取工具利用开源计算机视觉库(OpenCV)算法检测文本。该系统在超过25种发票上进行了测试,平均准确率在85%到95%之间。最后,为了方便使用,开发了一个web应用程序,该应用程序也以结构化格式呈现结果。整个系统的设计是为了提供灵活性和自动化从发票中提取感兴趣的详细信息的过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated invoice data extraction using image processing
Manually processing invoices which are in the form of scanned photocopies is a time-consuming process. There is a need to automate the task of extraction of data from the invoices with a similar format. In this paper we investigate and analyse various techniques of image processing and text extraction to improve the results of the optical character recognition (OCR) engine, which is applied to extract the text from the invoice. This paper also proposes the design and implementation of a web enabled invoice processing system (IPS). The IPS consists of an annotation tool and an extraction tool. The annotation tool is used to mark the fields of interest in the invoice which are to be extracted. The extraction tool makes use of opensource computer vision library (OpenCV) algorithms to detect text. The proposed system was tested on more than 25 types of invoices with the average accuracy score lying between 85% and 95%. Finally, to provide ease of use, a web application is developed which also presents the results in a structured format. The entire system is designed so as to provide flexibility and automate the process of extracting details of interest from the invoices.
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来源期刊
IAES International Journal of Artificial Intelligence
IAES International Journal of Artificial Intelligence Decision Sciences-Information Systems and Management
CiteScore
3.90
自引率
0.00%
发文量
170
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