{"title":"基于图像灰度特征的二维码图像校正研究","authors":"Muming Li, Peng Cao, Liuping Feng, Lifang Yu, Jianbo Chen, Jing Wang","doi":"10.1109/EIIS.2017.8298583","DOIUrl":null,"url":null,"abstract":"To solve the problem that traditional geometric correction algorithms of QR code will be influenced by light, shooting impact angle, correction algorithm robustness and so on, this paper proposes an adaptive algorithm based on image gray features, which achieves the accurate reading and rapid correction of QR code location information. After the pre-processing of QR code image, this algorithm calculates the dynamic threshold according to the gray value of feature image and the calculated threshold is used to confirm the most appropriate threshold of the QR location information. Then, we can get four accurate vertexes coordinates of QR code image and accomplish the accurate correction of QR code image based on projection transformation. The algorithm is able to complete effective correction for these captured images under different environments and solve the key technical bottlenecks of QR code recognition.","PeriodicalId":434246,"journal":{"name":"2017 First International Conference on Electronics Instrumentation & Information Systems (EIIS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"The research of QR code image correction based on image gray feature\",\"authors\":\"Muming Li, Peng Cao, Liuping Feng, Lifang Yu, Jianbo Chen, Jing Wang\",\"doi\":\"10.1109/EIIS.2017.8298583\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the problem that traditional geometric correction algorithms of QR code will be influenced by light, shooting impact angle, correction algorithm robustness and so on, this paper proposes an adaptive algorithm based on image gray features, which achieves the accurate reading and rapid correction of QR code location information. After the pre-processing of QR code image, this algorithm calculates the dynamic threshold according to the gray value of feature image and the calculated threshold is used to confirm the most appropriate threshold of the QR location information. Then, we can get four accurate vertexes coordinates of QR code image and accomplish the accurate correction of QR code image based on projection transformation. The algorithm is able to complete effective correction for these captured images under different environments and solve the key technical bottlenecks of QR code recognition.\",\"PeriodicalId\":434246,\"journal\":{\"name\":\"2017 First International Conference on Electronics Instrumentation & Information Systems (EIIS)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 First International Conference on Electronics Instrumentation & Information Systems (EIIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EIIS.2017.8298583\",\"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 First International Conference on Electronics Instrumentation & Information Systems (EIIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIIS.2017.8298583","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The research of QR code image correction based on image gray feature
To solve the problem that traditional geometric correction algorithms of QR code will be influenced by light, shooting impact angle, correction algorithm robustness and so on, this paper proposes an adaptive algorithm based on image gray features, which achieves the accurate reading and rapid correction of QR code location information. After the pre-processing of QR code image, this algorithm calculates the dynamic threshold according to the gray value of feature image and the calculated threshold is used to confirm the most appropriate threshold of the QR location information. Then, we can get four accurate vertexes coordinates of QR code image and accomplish the accurate correction of QR code image based on projection transformation. The algorithm is able to complete effective correction for these captured images under different environments and solve the key technical bottlenecks of QR code recognition.