吉林大学学报(信息科学版) ›› 2025, Vol. 43 ›› Issue (5): 1192-1199.

• • 上一篇    

财务票据图像污渍干扰下关键信息精准识别方法

李星宇,吴尚梅    

  1. 川北医学院计划财务处,四川南充637000
  • 收稿日期:2025-04-08 出版日期:2025-09-28 发布日期:2025-11-20
  • 作者简介:李星宇(1996— ), 男, 四川南充人, 川北医学院助教, 主要从事财务信息化研究, (Tel)86-15281798909(E-mail) lixingyu00112233@163. com。
  • 基金资助:
    川北医院2023年专项课题基金资助项目(2023QN007)

Accurate Recognition Method of Key Information under the Interference of Stains in Financial Bill Images

LI Xingyu, WU Shangmei   

  1. Finance Office, North Sichuan Medical College, Nanchong 637000, China
  • Received:2025-04-08 Online:2025-09-28 Published:2025-11-20

摘要: 为解决含污渍财务票据信息识别时因局部信息缺失或误判导致识别失败的问题,提出了一种新的财务票据图像污渍干扰下关键信息精准识别方法。 通过对图像的灰度和去噪整合,按照阈值大小,划分票据区域, 实现二值化处理。 利用感兴趣区域(ROI: Region of Interest)原理, 在二值化处理后的图像中进行信息范围的粗筛选,测算出最大包覆轮廓和关键信息粘连区域, 并对其进一步分割与边缘标定,依托于ROI比例,定位关键信息区域。 提取关键信息区域的特征,以端到端的方式结合特征建立分类标签,在覆盖识别区域中按照标签梯度搜索,完成识别目标的捕捉。 实验结果表明,所提方法得出的检索率80% ~100%之间,应用效率大幅度提升,性能优越可靠。

关键词: 财务票据, 图像污渍, 关键信息, 精准识别, 识别方法, 缺陷定位

Abstract: A new method for accurately identifying key information in financial bill images under the interference of stains is proposed to solve the problem of recognition failure caused by local information loss or misjudgment during the recognition of financial bill information containing stains. By integrating the gray scale and denoising of the image, dividing the bill area according to the threshold size, binary processing is achieved. Using the ROI (Region of Interest) principle, rough screening of information range is performed in the binary processed image to calculate the maximum coverage contour and key information adhesion area. Further segmentation and edge calibration are performed, and key information areas are located based on the ROI ratio. The features of key information areas is extracted, classification labels in an end-to-end manner are established by combining the features, and the recognition target is searched according to the label gradient in the coverage recognition area. The experimental results show that the retrieval rate obtained by the proposed method is between 80%-100%, and the efficiency is greatly improved with superior and reliable performance. 

Key words: financial receipts, image stains, key information, accurate identification, identification method, defect localization

中图分类号: 

  • TP391