{"title":"Research on automatic identification algorithm of invoice information","authors":"Liangyu Jiao, Hui Li","doi":"10.1117/12.3014488","DOIUrl":null,"url":null,"abstract":"The invoice reimbursement process is very cumbersome and requires manual entry of key information in the invoice, which wastes a lot of manpower and time. Therefore, it is particularly important to design an algorithm for intelligent identification of invoice information. Traditional algorithms can identify information from scanned invoice images. However, since in our country, most of the invoice information is Chinese characters, the current recognition algorithm has a certain degree of difficulty in identifying Chinese characters, and garbled characters will appear. Therefore, this article combines the CTPN text detection algorithm with the DesNets text recognition algorithm, and uses this algorithm to detect and recognize text on the information extracted from the invoice area image. Experiments show that the model outperforms the comparison model, with a recognition accuracy of up to 99.79%.","PeriodicalId":516634,"journal":{"name":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","volume":"25 3","pages":"129690U - 129690U-6"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.3014488","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The invoice reimbursement process is very cumbersome and requires manual entry of key information in the invoice, which wastes a lot of manpower and time. Therefore, it is particularly important to design an algorithm for intelligent identification of invoice information. Traditional algorithms can identify information from scanned invoice images. However, since in our country, most of the invoice information is Chinese characters, the current recognition algorithm has a certain degree of difficulty in identifying Chinese characters, and garbled characters will appear. Therefore, this article combines the CTPN text detection algorithm with the DesNets text recognition algorithm, and uses this algorithm to detect and recognize text on the information extracted from the invoice area image. Experiments show that the model outperforms the comparison model, with a recognition accuracy of up to 99.79%.