{"title":"基于空间直觉模糊c均值的三维CT图像缺陷体积测量算法","authors":"Li-ze Zhang, Kuan Shen","doi":"10.1109/FENDT54151.2021.9749668","DOIUrl":null,"url":null,"abstract":"Defect volume measurement of 3D computed tomography (CT) image is of great importance in defect analysis. Currently, there are few volumetric measurement algorithms for defects, and it is difficult to meet the requirements of practical applications. To address this issue, an automatic volumetric measurement algorithm is proposed to obtain the defect volume in a 3D CT image in a more precise way. Spatial intuitionistic fuzzy C-means (SIFCM) is used to segment the defects in each slice image. Compared with fuzzy C-means (FCM) and OTSU algorithms, defect segmentation can achieve better results and accuracy. Subsequently, the defect volume of the connected component can be calculated using the 3D region growing in the segmented binary images. The experimental results demonstrate the feasibility and effectiveness of the proposed algorithm, especially for large defects.","PeriodicalId":425658,"journal":{"name":"2021 IEEE Far East NDT New Technology & Application Forum (FENDT)","volume":"6 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Volumetric Measurement Algorithm of Defects in 3D CT Image Based on Spatial Intuitionistic Fuzzy C-means\",\"authors\":\"Li-ze Zhang, Kuan Shen\",\"doi\":\"10.1109/FENDT54151.2021.9749668\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Defect volume measurement of 3D computed tomography (CT) image is of great importance in defect analysis. Currently, there are few volumetric measurement algorithms for defects, and it is difficult to meet the requirements of practical applications. To address this issue, an automatic volumetric measurement algorithm is proposed to obtain the defect volume in a 3D CT image in a more precise way. Spatial intuitionistic fuzzy C-means (SIFCM) is used to segment the defects in each slice image. Compared with fuzzy C-means (FCM) and OTSU algorithms, defect segmentation can achieve better results and accuracy. Subsequently, the defect volume of the connected component can be calculated using the 3D region growing in the segmented binary images. The experimental results demonstrate the feasibility and effectiveness of the proposed algorithm, especially for large defects.\",\"PeriodicalId\":425658,\"journal\":{\"name\":\"2021 IEEE Far East NDT New Technology & Application Forum (FENDT)\",\"volume\":\"6 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Far East NDT New Technology & Application Forum (FENDT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FENDT54151.2021.9749668\",\"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 IEEE Far East NDT New Technology & Application Forum (FENDT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FENDT54151.2021.9749668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Volumetric Measurement Algorithm of Defects in 3D CT Image Based on Spatial Intuitionistic Fuzzy C-means
Defect volume measurement of 3D computed tomography (CT) image is of great importance in defect analysis. Currently, there are few volumetric measurement algorithms for defects, and it is difficult to meet the requirements of practical applications. To address this issue, an automatic volumetric measurement algorithm is proposed to obtain the defect volume in a 3D CT image in a more precise way. Spatial intuitionistic fuzzy C-means (SIFCM) is used to segment the defects in each slice image. Compared with fuzzy C-means (FCM) and OTSU algorithms, defect segmentation can achieve better results and accuracy. Subsequently, the defect volume of the connected component can be calculated using the 3D region growing in the segmented binary images. The experimental results demonstrate the feasibility and effectiveness of the proposed algorithm, especially for large defects.