Research on All-content Text Recognition Method for Financial Ticket Image

TL;DR

This paper presents a deep learning-based method for all-content text detection and recognition in financial tickets, achieving high accuracy and efficiency to improve financial accounting processes.

Contribution

It introduces a novel all-content text recognition method and a specialized framework for Chinese character recognition tailored to financial tickets.

Findings

Recognition accuracy of 91.75% for character sequences

Recognition accuracy of 87% for entire tickets

Significant efficiency improvement in financial accounting systems

Abstract

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.