{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:15:13Z","timestamp":1760242513487,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2017,10,6]],"date-time":"2017-10-06T00:00:00Z","timestamp":1507248000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Remote-Field Eddy-Current (RFEC) technology is often used as a Non-Destructive Evaluation (NDE) method to prevent water pipe failures. By analyzing the RFEC data, it is possible to quantify the corrosion present in pipes. Quantifying the corrosion involves detecting defects and extracting their depth and shape. For large sections of pipelines, this can be extremely time-consuming if performed manually. Automated approaches are therefore well motivated. In this article, we propose an automated framework to locate and segment defects in individual pipe segments, starting from raw RFEC measurements taken over large pipelines. The framework relies on a novel feature to robustly detect these defects and a segmentation algorithm applied to the deconvolved RFEC signal. The framework is evaluated using both simulated and real datasets, demonstrating its ability to efficiently segment the shape of corrosion defects.<\/jats:p>","DOI":"10.3390\/s17102276","type":"journal-article","created":{"date-parts":[[2017,10,6]],"date-time":"2017-10-06T10:56:34Z","timestamp":1507287394000},"page":"2276","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Defect Detection and Segmentation Framework for Remote Field Eddy Current Sensor Data"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4436-647X","authenticated-orcid":false,"given":"Raphael","family":"Falque","sequence":"first","affiliation":[{"name":"Centre for Autonomous Systems (CB 11.09.300), Faculty of Engineering and Information Technology, University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5763-9644","authenticated-orcid":false,"given":"Teresa","family":"Vidal-Calleja","sequence":"additional","affiliation":[{"name":"Centre for Autonomous Systems (CB 11.09.300), Faculty of Engineering and Information Technology, University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0083-7797","authenticated-orcid":false,"given":"Jaime","family":"Miro","sequence":"additional","affiliation":[{"name":"Centre for Autonomous Systems (CB 11.09.300), Faculty of Engineering and Information Technology, University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,10,6]]},"reference":[{"key":"ref_1","unstructured":"MacLean, W.R. (1951). Apparatus for Magnetically Measuring Thinckness of Ferrous Pipe. (2573799), U.S. Patent."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1109\/20.43950","article-title":"A finite element study of the remote field eddy current phenomen","volume":"24","author":"Lord","year":"1988","journal-title":"IEEE Trans. Magn."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2663","DOI":"10.1109\/TMAG.1987.1065698","article-title":"Electromagnetic field calculations for the low frequency eddy current testing of tubular products","volume":"23","author":"Palanisamy","year":"1987","journal-title":"IEEE Trans. Magn."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1115\/1.1991878","article-title":"Small diameter remote field eddy current inspection for unpiggable pipelines","volume":"127","author":"Teitsma","year":"2005","journal-title":"J. Press. Vessel Technol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3006","DOI":"10.1088\/0957-0233\/17\/11\/021","article-title":"Robust estimation of flaw dimensions using remote field eddy current inspection","volume":"17","author":"Davoust","year":"2006","journal-title":"Meas. Sci. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1080\/09349849908968148","article-title":"A parametric estimation approach for groove dimensioning using remote field eddy current inspection","volume":"11","author":"Davoust","year":"1999","journal-title":"Res. Nondestr. Eval."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Saranya, R., Jackson, D., Abudhahir, A., and Chermakani, N. (2014, January 13\u201314). Comparison of segmentation techniques for detection of defects in non-destructive testing images. Proceedings of the 2014 International Conference on Electronics and Communication Systems (ICECS), Coimbatore, India.","DOI":"10.1109\/ECS.2014.6892787"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Falque, R., Vidal-Calleja, T., Dissanayake, G., and Miro, J.V. (2016, January 13\u201315). From the skin-depth equation to the inverse RFEC sensor model. Proceedings of the 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), Phuket, Thailand.","DOI":"10.1109\/ICARCV.2016.7838633"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Luo, Q.W., Shi, Y.B., Wang, Z.G., Zhang, W., and Zhang, Y. (2016). Approach for removing ghost-images in remote field eddy current testing of ferromagnetic pipes. Rev. Sci. Instrum., 87.","DOI":"10.1063\/1.4964374"},{"key":"ref_10","unstructured":"Falque, R., Vidal-Calleja, T., and Valls Miro, J. (2017). Towards Inverse modeling of RFEC via an optimization based signal deconvolution. arXiV, preprint."},{"key":"ref_11","unstructured":"Zhang, Y. (1997). Electric and Magnetic Contributions and Defect Interactions in Remote Field Eddy Current Techniques. [Ph.D. Thesis, Queen\u2019s University]."},{"key":"ref_12","unstructured":"Falque, R., Vidal-Calleja, T., Valls Miro, J., Lingnau, D.C., and Russell, D.E. (2014, January 2\u20134). Background segmentation to enhance remote field eddy current signals. Proceedings of the Australasian Conference on Robotics and Automation (ACRA), Melbourne, Australia."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Vidal-Calleja, T., Miro, J.V., Martin, F., Lingnau, D.C., and Russell, D.E. (2014, January 14\u201318). Automatic detection and verification of pipeline construction features with multi-modal data. Proceedings of the 2014 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, USA.","DOI":"10.1109\/IROS.2014.6942993"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1016\/0013-4694(70)90143-4","article-title":"EEG analysis based on time domain properties","volume":"29","author":"Hjorth","year":"1970","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"key":"ref_15","unstructured":"Rish, I. (2001). An Empirical Study of the Naive Bayes Classifier, IBM Research\u2014Thomas J. Watson Research Center. Technical Report."},{"key":"ref_16","unstructured":"Russell, Stuart, J., and Norvig, P. (2009). Artificial Intelligence: A Modern Approach, Prentice Hall."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1111\/j.2517-6161.1958.tb00292.x","article-title":"The regression analysis of binary sequences","volume":"20","author":"Cox","year":"1958","journal-title":"J. R. Stat. Soc. Ser. B Methodol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1097\/00005373-198704000-00005","article-title":"Evaluating Trauma Care","volume":"27","author":"Boyd","year":"1987","journal-title":"J. Trauma Inj. Infect. Crit. Care"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1016\/0021-9681(67)90082-3","article-title":"A multivariate analysis of the risk of coronary heart disease in Framingham","volume":"20","author":"Truett","year":"1967","journal-title":"J. Chronic Dis."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Harrell, F.E. (2001). Regression Modeling Strategies, Springer.","DOI":"10.1007\/978-1-4757-3462-1"},{"key":"ref_21","unstructured":"Ho, T.K. (1995, January 14\u201316). Random decision forests. Proceedings of the 3rd International Conference on Document Analysis and Recognition, Montreal, QC, Canada."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Hastie, T., Tibshirani, R., and Friedman, J. (2009). The Elements of Statistical Learning, Springer.","DOI":"10.1007\/978-0-387-84858-7"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1214\/009053607000000677","article-title":"Kernel methods in machine learning","volume":"36","author":"Hofmann","year":"2008","journal-title":"Ann. Stat."},{"key":"ref_25","first-page":"3133","article-title":"Do we need hundreds of classifiers to solve real world classification problems?","volume":"15","author":"Cernadas","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref_26","unstructured":"Cormen, T.H., Leiserson, C.E., Rivest, R., and Stein, C. (2009). Introduction to Algorithms, MIT Press."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1109\/83.902291","article-title":"Active contours without edges","volume":"10","author":"Chan","year":"2001","journal-title":"IEEE Trans. Image Process."},{"key":"ref_28","unstructured":"Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley Longman Publishing Co., Inc."},{"key":"ref_29","unstructured":"Shi, L., Sun, L., Vidal Calleja, T., and Valls Miro, J. (2015, January 2\u20134). Kernel-specific gaussian process for predicting pipe wall thickness maps. Proceedings of the Australasian Conference on Robotics and Automation, Canberra, Australia."},{"key":"ref_30","unstructured":"Skinner, B., Vidal-Calleja, T., Valls Miro, J., Bruijn, F.D., and Falque, R. (2014, January 2\u20134). 3D point cloud upsampling for accurate reconstruction of dense 2.5D thickness maps. Proceedings of the Australasian Conference on Robotics and Automation (ACRA), Melbourne, Australia."},{"key":"ref_31","unstructured":"Falque, R., Vidal-Calleja, T., and Miro, J.V. (October, January 28). Kidnapped laser-scanner for evaluation of RFEC tool. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1177\/001316446002000104","article-title":"A coefficient of agreement for nominal scales","volume":"20","author":"Cohen","year":"1960","journal-title":"Educ. Psychol. Meas."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1016\/j.patrec.2005.10.010","article-title":"An introduction to ROC analysis","volume":"27","author":"Fawcett","year":"2006","journal-title":"Pattern Recognit. Lett."},{"key":"ref_34","unstructured":"Platt, J.C. (1998). Sequential Minimal Optimization: A Fast Algorithm for Training Support Vector Machines, Microsoft Research. Technical Report MSR-TR-98-14."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1109\/TPAMI.2011.130","article-title":"Image segmentation by probabilistic bottom-up aggregation and cue integration","volume":"34","author":"Alpert","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_37","first-page":"1","article-title":"Contour detection and hierarchical image segmentation","volume":"33","author":"Arbel","year":"2011","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Ulapane, N., Alempijevic, A., Vidal-Calleja, T., Miro, J.V., Rudd, J., and Roubal, M. (2014, January 9\u201311). Gaussian process for interpreting pulsed eddy current signals for ferromagnetic pipe profiling. Proceedings of the 2014 IEEE 9th Conference on Industrial Electronics and Applications (ICIEA), Hangzhou, China.","DOI":"10.1109\/ICIEA.2014.6931453"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1023\/B:VISI.0000022288.19776.77","article-title":"Efficient graph-based image segmentation","volume":"59","author":"Felzenszwalb","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Long, J., Shelhamer, E., and Darrell, T. (2015, January 7\u201312). Fully convolutional networks for semantic segmentation. Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ress.2003.12.007","article-title":"Probabilistic risk analysis of corrosion associated failures in cast iron water mains","volume":"86","author":"Sadiq","year":"2004","journal-title":"Reliab. Eng. Syst. Saf."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/10\/2276\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:46:39Z","timestamp":1760208399000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/10\/2276"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10,6]]},"references-count":41,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2017,10]]}},"alternative-id":["s17102276"],"URL":"https:\/\/doi.org\/10.3390\/s17102276","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2017,10,6]]}}}