{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T19:17:53Z","timestamp":1773775073795,"version":"3.50.1"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2021,5,10]],"date-time":"2021-05-10T00:00:00Z","timestamp":1620604800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,5,10]],"date-time":"2021-05-10T00:00:00Z","timestamp":1620604800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100011170","name":"Jiangsu Key Laboratory of Fine Petrochemical Engineering","doi-asserted-by":"crossref","award":["( DT2020720"],"award-info":[{"award-number":["( DT2020720"]}],"id":[{"id":"10.13039\/501100011170","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100011170","name":"Jiangsu Key Laboratory of Fine Petrochemical Engineering","doi-asserted-by":"publisher","award":["(DTEC202001,DT2020720)"],"award-info":[{"award-number":["(DTEC202001,DT2020720)"]}],"id":[{"id":"10.13039\/501100011170","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2022,8]]},"DOI":"10.1007\/s00371-021-02148-9","type":"journal-article","created":{"date-parts":[[2021,5,10]],"date-time":"2021-05-10T02:02:21Z","timestamp":1620612141000},"page":"2707-2721","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Low-rank decomposition fabric defect detection based on prior and total variation regularization"],"prefix":"10.1007","volume":"38","author":[{"given":"Xiangyang","family":"Bao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiuzhen","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunfei","family":"Xia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenjie","family":"Hou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhan","family":"Huan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,5,10]]},"reference":[{"issue":"1","key":"2148_CR1","doi-asserted-by":"publisher","first-page":"79","DOI":"10.13074\/jent.2017.03.171241","volume":"6","author":"SS Selvi","year":"2017","unstructured":"Selvi, S.S., Nasira, G.M.: An effective automatic fabric defect detection system using digital image processing. J. Environ. Nanotechnol. 6(1), 79\u201385 (2017)","journal-title":"J. Environ. Nanotechnol."},{"key":"2148_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2015.09.022","volume-title":"Fabric Inspection Based on the Elo Rating Method","author":"CSC Tsang","year":"2016","unstructured":"Tsang, C.S.C., Ngan, H.Y.T., Pang, G.K.H.: Fabric Inspection Based on the Elo Rating Method. Elsevier, Amsterdam (2016)"},{"issue":"8","key":"2148_CR3","doi-asserted-by":"publisher","first-page":"087202","DOI":"10.1117\/1.2345189","volume":"45","author":"HYT Ngan","year":"2006","unstructured":"Ngan, H.Y.T., Pang, G.K.H.: Novel method for patterned fabric inspection using Bollinger bands. Opt. Eng. 45(8), 087202 (2006)","journal-title":"Opt. Eng."},{"issue":"1","key":"2148_CR4","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1109\/TASE.2008.917140","volume":"6","author":"HYT Ngan","year":"2008","unstructured":"Ngan, H.Y.T., Pang, G.K.H.: Regularity analysis for patterned texture inspection. IEEE Trans. Autom. Sci. Eng. 6(1), 131\u2013144 (2008)","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"issue":"4","key":"2148_CR5","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1016\/j.patcog.2004.07.009","volume":"38","author":"HYT Ngan","year":"2005","unstructured":"Ngan, H.Y.T., et al.: Wavelet based methods on patterned fabric defect detection. Pattern Recognit. 38(4), 559\u2013576 (2005)","journal-title":"Pattern Recognit."},{"key":"2148_CR6","unstructured":"Ngan, H.Y.T., Pang, G.K.H, Yung, S.P., et\u00a0al.: Defect detection on patterned jacquard fabric. In: Applied Imagery Pattern Recognition Workshop (2003)"},{"key":"2148_CR7","first-page":"1","volume":"2018","author":"X Chang","year":"2018","unstructured":"Chang, X., Gu, C., Liang, J., et al.: Fabric defect detection based on pattern template correction. Math. Probl. Eng. 2018, 1\u201317 (2018)","journal-title":"Math. Probl. Eng."},{"issue":"3","key":"2148_CR8","doi-asserted-by":"publisher","first-page":"943","DOI":"10.1109\/TASE.2014.2314240","volume":"11","author":"MK Ng","year":"2014","unstructured":"Ng, M.K., et al.: Patterned fabric inspection and visualization by the method of image decomposition. IEEE Trans. Autom. Sci. Eng. 11(3), 943\u2013947 (2014)","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"issue":"4","key":"2148_CR9","doi-asserted-by":"publisher","first-page":"2140","DOI":"10.1137\/17M1113138","volume":"10","author":"MK Ng","year":"2017","unstructured":"Ng, M.K., et al.: Lattice-based patterned fabric inspection by using total variation with sparsity and low-rank representations. SIAM J. Imaging Sci. 10(4), 2140\u20132164 (2017)","journal-title":"SIAM J. Imaging Sci."},{"key":"2148_CR10","first-page":"155892502095765","volume":"15","author":"X Ji","year":"2020","unstructured":"Ji, X., Liang, J., Di, L., et al.: Fabric defect fetection via weighted low-rank decomposition and Laplacian regularization. J. Eng. Fibers Fabr. 15, 1558925020957654 (2020)","journal-title":"J. Eng. Fibers Fabr."},{"key":"2148_CR11","doi-asserted-by":"publisher","first-page":"83962","DOI":"10.1109\/ACCESS.2019.2925196","volume":"7","author":"C Li","year":"2019","unstructured":"Li, C., et al.: Defect detection for patterned fabric images based on GHOG and low-rank decomposition. IEEE Access 7, 83962\u201383973 (2019)","journal-title":"IEEE Access"},{"key":"2148_CR12","doi-asserted-by":"crossref","unstructured":"Liu, G., Zheng, X.: Fabric defect detection based on information entropy and frequency domain saliency. Vis. Comput. 24 (2020)","DOI":"10.1007\/s00371-020-01820-w"},{"issue":"68","key":"2148_CR13","first-page":"10611071","volume":"33","author":"L Bi","year":"2017","unstructured":"Bi, L., Kim, J., Kumar, A., Fulham, M., Feng, D.: Stacked fully convolutional networks with multi-channel learning: application to medical image segmentation. Vis. Comput. 33(68), 10611071 (2017)","journal-title":"Vis. Comput."},{"key":"2148_CR14","doi-asserted-by":"crossref","unstructured":"Yuan, H. et\u00a0al.: A deep convolutional neural network for detection of rail surface defect. In: 2019 IEEE Vehicle Power and Propulsion Conference (VPPC). IEEE (2019)","DOI":"10.1109\/VPPC46532.2019.8952236"},{"key":"2148_CR15","doi-asserted-by":"publisher","first-page":"1678","DOI":"10.3390\/app8091678","volume":"8","author":"Y Li","year":"2018","unstructured":"Li, Y., Huang, H., Xie, Q., Yao, L., Chen, Q.: Research on a surface defect detection algorithm based on MobileNet-SSD. Appl. Sci. 8, 1678 (2018)","journal-title":"Appl. Sci."},{"key":"2148_CR16","doi-asserted-by":"crossref","unstructured":"Bergmann, P., et\u00a0al.: Improving unsupervised defect segmentation by applying structural similarity to autoencoders. arXiv:1807.02011 (2019)","DOI":"10.5220\/0007364503720380"},{"key":"2148_CR17","doi-asserted-by":"crossref","unstructured":"Gong, D., Liu, L., Le, V., et\u00a0al.: Memorizing normality to detect anomaly: memory-augmented deep autoencoder for unsupervised anomaly detection. In: 2019 IEEE\/CVF International Conference on Computer Vision (ICCV). IEEE (2020)","DOI":"10.1109\/ICCV.2019.00179"},{"key":"2148_CR18","doi-asserted-by":"publisher","first-page":"335347","DOI":"10.1007\/s00371-017-1463-9","volume":"35","author":"JH Giraldo-Zuluaga","year":"2019","unstructured":"Giraldo-Zuluaga, J.H., Salazar, A., Gomez, A., et al.: Camera-trap images segmentation using multi-layer robust principal component analysis. Vis. Comput. 35, 335347 (2019)","journal-title":"Vis. Comput."},{"issue":"4","key":"2148_CR19","doi-asserted-by":"publisher","first-page":"516529","DOI":"10.1108\/IJCST-10-2015-0117","volume":"28","author":"J Cao","year":"2016","unstructured":"Cao, J., Wang, N., Zhang, J., Wen, Z., Li, B., Liu, X.: Detection of varied defects in diverse fabric images via modified RPCA with noise term and defect prior. Int. J. Clothing Sci. Technol. 28(4), 516529 (2016)","journal-title":"Int. J. Clothing Sci. Technol."},{"key":"2148_CR20","doi-asserted-by":"crossref","unstructured":"Liu, G., Li, F.: Fabric defect detection based on low-rank decomposition with structural constraints. Vis. Comput. (2021)","DOI":"10.1007\/s00371-020-02040-y"},{"issue":"3","key":"2148_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1970392.1970395","volume":"58","author":"EJ Candes","year":"2011","unstructured":"Candes, E.J., Li, X., Ma, Y., et al.: Robust principal component analysis. J. ACM 58(3), 1\u201337 (2011)","journal-title":"J. ACM"},{"issue":"4","key":"2148_CR22","doi-asserted-by":"publisher","first-page":"600612","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600612 (2004)","journal-title":"IEEE Trans. Image Process."},{"key":"2148_CR23","doi-asserted-by":"crossref","unstructured":"Rudin, L.I., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. In: Eleventh International Conference of the Center for Nonlinear Studies on Experimental Mathematics: Computational Issues in Nonlinear Science: Computational Issues in Nonlinear Science. Elsevier North-Holland, Inc. (1992)","DOI":"10.1016\/0167-2789(92)90242-F"},{"issue":"11","key":"2148_CR24","doi-asserted-by":"publisher","first-page":"3502","DOI":"10.1016\/j.patcog.2014.05.001","volume":"47","author":"Z Zheng","year":"2014","unstructured":"Zheng, Z., Yu, M., Jia, J., et al.: Fisher discrimination based low rank matrix recovery for face recognition. Pattern Recognit 47(11), 3502\u20133511 (2014)","journal-title":"Pattern Recognit"},{"issue":"4","key":"2148_CR25","doi-asserted-by":"publisher","first-page":"1956","DOI":"10.1137\/080738970","volume":"20","author":"JF Cai","year":"2010","unstructured":"Cai, J.F., Cands, E.J., Shen, Z.: A singular value thresholding algorithm for matrix completion. SIAM J. Optim. 20(4), 1956\u20131982 (2010)","journal-title":"SIAM J. Optim."},{"issue":"1","key":"2148_CR26","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1137\/080716542","volume":"2","author":"A Beck","year":"2009","unstructured":"Beck, A., Teboulle, M.: A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Imaging Sci. 2(1), 183\u2013202 (2009)","journal-title":"SIAM J. Imaging Sci."},{"issue":"2","key":"2148_CR27","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1137\/080725891","volume":"2","author":"T Goldstein","year":"2009","unstructured":"Goldstein, T., Osher, S.: The split Bregman method for L1-regularized problems. SIAM J. Imaging Sci. 2(2), 323\u2013343 (2009)","journal-title":"SIAM J. Imaging Sci."},{"key":"2148_CR28","first-page":"016","volume":"10","author":"L Zhoufeng","year":"2013","unstructured":"Zhoufeng, L., Jiuge, W., Quanjun, Z., et al.: Research on fabric defect detection algorithm based on improved adaptive threshold. Microcomput. Appl. 10, 016 (2013)","journal-title":"Microcomput. Appl."},{"issue":"4","key":"2148_CR29","doi-asserted-by":"publisher","first-page":"1064","DOI":"10.3390\/s18041064","volume":"18","author":"S Mei","year":"2018","unstructured":"Mei, S., Wang, Y., Wen, G.: Automatic fabric defect detection with a multi-scale convolutional denoising autoencoder network model. Sensors 18(4), 1064 (2018)","journal-title":"Sensors"},{"issue":"10","key":"2148_CR30","doi-asserted-by":"publisher","first-page":"14891500","DOI":"10.1007\/s00371-018-1513-y","volume":"35","author":"L Doyle","year":"2019","unstructured":"Doyle, L., Mould, D.: Augmenting photographs with textures using the Laplacian pyramid. Vis. Comput. 35(10), 14891500 (2019)","journal-title":"Vis. Comput."},{"key":"2148_CR31","unstructured":"Kingma, D.P., Ba, J.: A method for stochastic optimization. In: International Conference on Learning Representations (2015)"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-021-02148-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-021-02148-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-021-02148-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,19]],"date-time":"2022-07-19T09:08:04Z","timestamp":1658221684000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-021-02148-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,10]]},"references-count":31,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2022,8]]}},"alternative-id":["2148"],"URL":"https:\/\/doi.org\/10.1007\/s00371-021-02148-9","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,10]]},"assertion":[{"value":"23 April 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 May 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}