Artjoms Suponenkovs, A. Sisojevs, Guntis Mosans, Jānis Kampars, Krisjanis Pinka, J. Grabis, A. Ločmelis, R. Taranovs
{"title":"图像识别和机器学习技术在支付数据处理中的应用综述与挑战","authors":"Artjoms Suponenkovs, A. Sisojevs, Guntis Mosans, Jānis Kampars, Krisjanis Pinka, J. Grabis, A. Ločmelis, R. Taranovs","doi":"10.1109/AIEEE.2017.8270536","DOIUrl":null,"url":null,"abstract":"The automatic receipt analysis problem is very relevant due to high cost of manual document processing. Therefore, the presented paper investigates the problems of receipt image analysis. It describes approaches for receipt image pre-processing, receipt text detection, receipt text recognition and receipt text analysis. These approaches allow to make receipt analysis system adaptable for a real-life environment and to convert the input information to a usable format for analysing information in the receipts. A pipeline for payment data processing staring with image capture to payment data posting is defined and appropriate technologies for every stage of the process are proposed. Advantages and limitations of these technologies are reviewed and open research challenges are identified. The payment data processing is analyzed as an enabler of digital transformation of expense reporting processes.","PeriodicalId":224275,"journal":{"name":"2017 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Application of image recognition and machine learning technologies for payment data processing review and challenges\",\"authors\":\"Artjoms Suponenkovs, A. Sisojevs, Guntis Mosans, Jānis Kampars, Krisjanis Pinka, J. Grabis, A. Ločmelis, R. Taranovs\",\"doi\":\"10.1109/AIEEE.2017.8270536\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The automatic receipt analysis problem is very relevant due to high cost of manual document processing. Therefore, the presented paper investigates the problems of receipt image analysis. It describes approaches for receipt image pre-processing, receipt text detection, receipt text recognition and receipt text analysis. These approaches allow to make receipt analysis system adaptable for a real-life environment and to convert the input information to a usable format for analysing information in the receipts. A pipeline for payment data processing staring with image capture to payment data posting is defined and appropriate technologies for every stage of the process are proposed. Advantages and limitations of these technologies are reviewed and open research challenges are identified. The payment data processing is analyzed as an enabler of digital transformation of expense reporting processes.\",\"PeriodicalId\":224275,\"journal\":{\"name\":\"2017 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE)\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIEEE.2017.8270536\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIEEE.2017.8270536","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of image recognition and machine learning technologies for payment data processing review and challenges
The automatic receipt analysis problem is very relevant due to high cost of manual document processing. Therefore, the presented paper investigates the problems of receipt image analysis. It describes approaches for receipt image pre-processing, receipt text detection, receipt text recognition and receipt text analysis. These approaches allow to make receipt analysis system adaptable for a real-life environment and to convert the input information to a usable format for analysing information in the receipts. A pipeline for payment data processing staring with image capture to payment data posting is defined and appropriate technologies for every stage of the process are proposed. Advantages and limitations of these technologies are reviewed and open research challenges are identified. The payment data processing is analyzed as an enabler of digital transformation of expense reporting processes.