{"title":"基于模型的矩形变换裂缝宽度估计","authors":"C. Benz, V. Rodehorst","doi":"10.23919/MVA51890.2021.9511346","DOIUrl":null,"url":null,"abstract":"The automated image-based robust estimation of crack widths in concrete structures forms a significant component in the automation of structural health monitoring. The proposed method, called rectangle transform, uses the gray-scale profile extracted perpendicularly to the direction of crack propagation. Based on the concept of an idealized profile, it transforms the empirical profile into an equal-area rectangle from which the width is inferred. On the available dataset and compared to two other approaches, it shows at least par performance for widths larger two pixels and distinctly better performance on widths smaller equal two pixels. Moreover, it is more robust towards blurred input.","PeriodicalId":312481,"journal":{"name":"2021 17th International Conference on Machine Vision and Applications (MVA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Model-based Crack Width Estimation using Rectangle Transform\",\"authors\":\"C. Benz, V. Rodehorst\",\"doi\":\"10.23919/MVA51890.2021.9511346\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The automated image-based robust estimation of crack widths in concrete structures forms a significant component in the automation of structural health monitoring. The proposed method, called rectangle transform, uses the gray-scale profile extracted perpendicularly to the direction of crack propagation. Based on the concept of an idealized profile, it transforms the empirical profile into an equal-area rectangle from which the width is inferred. On the available dataset and compared to two other approaches, it shows at least par performance for widths larger two pixels and distinctly better performance on widths smaller equal two pixels. Moreover, it is more robust towards blurred input.\",\"PeriodicalId\":312481,\"journal\":{\"name\":\"2021 17th International Conference on Machine Vision and Applications (MVA)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 17th International Conference on Machine Vision and Applications (MVA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/MVA51890.2021.9511346\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 17th International Conference on Machine Vision and Applications (MVA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/MVA51890.2021.9511346","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Model-based Crack Width Estimation using Rectangle Transform
The automated image-based robust estimation of crack widths in concrete structures forms a significant component in the automation of structural health monitoring. The proposed method, called rectangle transform, uses the gray-scale profile extracted perpendicularly to the direction of crack propagation. Based on the concept of an idealized profile, it transforms the empirical profile into an equal-area rectangle from which the width is inferred. On the available dataset and compared to two other approaches, it shows at least par performance for widths larger two pixels and distinctly better performance on widths smaller equal two pixels. Moreover, it is more robust towards blurred input.