{"title":"利用数字图像处理技术实现射线照相胶片焊缝缺陷的自动检测","authors":"Ngon Dang Thien, C. L. Chi, Ha Nguyen Ngoc","doi":"10.1109/ICSSE.2017.8030899","DOIUrl":null,"url":null,"abstract":"Oil refinery industry is using large amount of radiographic films of weld defects, requiring human work by technicians to interpretation. This paper presents a method and automated system for determination of weld defect from radiographic films by using the image processing technique. The hardware and software system rapidly and automatically convert the radiographic films into digital images, then analyzes and compares with the digitalized radiographic images database. The probable defects and its type recognized defect are determined. This approach will be significant in developing a professional system for partially replacing technician work in image interpretation, ensuring quality and productivity in welding manufacturing technology.","PeriodicalId":296191,"journal":{"name":"2017 International Conference on System Science and Engineering (ICSSE)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"An approach to the automatic detection of weld defects in radiography films using digital image processing\",\"authors\":\"Ngon Dang Thien, C. L. Chi, Ha Nguyen Ngoc\",\"doi\":\"10.1109/ICSSE.2017.8030899\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Oil refinery industry is using large amount of radiographic films of weld defects, requiring human work by technicians to interpretation. This paper presents a method and automated system for determination of weld defect from radiographic films by using the image processing technique. The hardware and software system rapidly and automatically convert the radiographic films into digital images, then analyzes and compares with the digitalized radiographic images database. The probable defects and its type recognized defect are determined. This approach will be significant in developing a professional system for partially replacing technician work in image interpretation, ensuring quality and productivity in welding manufacturing technology.\",\"PeriodicalId\":296191,\"journal\":{\"name\":\"2017 International Conference on System Science and Engineering (ICSSE)\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on System Science and Engineering (ICSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSE.2017.8030899\",\"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 International Conference on System Science and Engineering (ICSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSE.2017.8030899","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An approach to the automatic detection of weld defects in radiography films using digital image processing
Oil refinery industry is using large amount of radiographic films of weld defects, requiring human work by technicians to interpretation. This paper presents a method and automated system for determination of weld defect from radiographic films by using the image processing technique. The hardware and software system rapidly and automatically convert the radiographic films into digital images, then analyzes and compares with the digitalized radiographic images database. The probable defects and its type recognized defect are determined. This approach will be significant in developing a professional system for partially replacing technician work in image interpretation, ensuring quality and productivity in welding manufacturing technology.