{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T19:04:50Z","timestamp":1768417490102,"version":"3.49.0"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2017,5,6]],"date-time":"2017-05-06T00:00:00Z","timestamp":1494028800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2018,5]]},"DOI":"10.1007\/s00371-017-1367-8","type":"journal-article","created":{"date-parts":[[2017,5,6]],"date-time":"2017-05-06T04:17:14Z","timestamp":1494044234000},"page":"617-632","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Robust cost function for optimizing chamfer masks"],"prefix":"10.1007","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7551-0107","authenticated-orcid":false,"given":"Baraka Jacob","family":"Maiseli","sequence":"first","affiliation":[]},{"given":"LiFei","family":"Bai","sequence":"additional","affiliation":[]},{"given":"Xianqiang","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Yanfeng","family":"Gu","sequence":"additional","affiliation":[]},{"given":"Huijun","family":"Gao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,5,6]]},"reference":[{"key":"1367_CR1","doi-asserted-by":"publisher","unstructured":"Song, C., Pang, Z., Jing, X., Xiao, C.: Distance field guided L_1-median skeleton extraction. Vis. Comput. 1\u201313 (2016). doi: 10.1007\/s00371-016-1331-z","DOI":"10.1007\/s00371-016-1331-z"},{"key":"1367_CR2","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.patrec.2015.04.006","volume":"76","author":"PK Saha","year":"2016","unstructured":"Saha, P.K., Borgefors, G., di Baja, G.S.: A survey on skeletonization algorithms and their applications. Pattern Recognit. Lett. 76, 3\u201312 (2016)","journal-title":"Pattern Recognit. Lett."},{"key":"1367_CR3","doi-asserted-by":"crossref","unstructured":"Coeurjolly, D., Montanvert, A.: Optimal separable algorithms to compute the reverse Euclidean distance transformation and discrete medial axis in arbitrary dimension. arXiv:0705.3343 (2007)","DOI":"10.1109\/TPAMI.2007.54"},{"issue":"2","key":"1367_CR4","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1109\/TPAMI.2003.1177156","volume":"25","author":"CR Maurer","year":"2003","unstructured":"Maurer, C.R., Qi, R., Raghavan, V.: A linear time algorithm for computing exact Euclidean distance transforms of binary images in arbitrary dimensions. IEEE Trans. Pattern Anal. Mach. Intell. 25(2), 265\u2013270 (2003)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1367_CR5","doi-asserted-by":"publisher","unstructured":"Bailey, D.G.: An efficient Euclidean distance transform. In: International Workshop on Combinatorial Image Analysis, pp. 394\u2013408. Springer (2004). doi: 10.1007\/978-3-540-30503-3_28","DOI":"10.1007\/978-3-540-30503-3_28"},{"issue":"5","key":"1367_CR6","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1109\/34.391389","volume":"17","author":"H Breu","year":"1995","unstructured":"Breu, H., Gil, J., Kirkpatrick, D., Werman, M.: Linear time Euclidean distance transform algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 17(5), 529\u2013533 (1995)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1367_CR7","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s00371-014-1053-z","volume":"32","author":"H Zhang","year":"2016","unstructured":"Zhang, H., Xu, M., Zhuo, L., Havyarimana, V.: A novel optimization framework for salient object detection. Vis. Comput. 32, 31\u201341 (2016)","journal-title":"Vis. Comput."},{"issue":"9\u201311","key":"1367_CR8","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1007\/s00371-006-0054-y","volume":"22","author":"Y Weng","year":"2006","unstructured":"Weng, Y., Xu, W., Wu, Y., Zhou, K., Guo, B.: 2D shape deformation using nonlinear least squares optimization. Vis. Comput. 22(9\u201311), 653\u2013660 (2006)","journal-title":"Vis. Comput."},{"key":"1367_CR9","doi-asserted-by":"publisher","unstructured":"Ding, S., Sheng, B., Xie, Z., Ma, L.: Intrinsic image estimation using near-L_0 sparse optimization. Vis. Comput. 33, 1\u201315 (2016). doi: 10.1007\/s00371-015-1205-9","DOI":"10.1007\/s00371-015-1205-9"},{"issue":"7","key":"1367_CR10","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1007\/s00371-007-0122-y","volume":"23","author":"A Mu\u00f1oz","year":"2007","unstructured":"Mu\u00f1oz, A., Gutierrez, D., Ser\u00f3n, F.J.: Optimization techniques for curved path computing. Vis. Comput. 23(7), 493\u2013502 (2007)","journal-title":"Vis. Comput."},{"key":"1367_CR11","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1109\/MSP.2008.930649","volume":"26","author":"Z Wang","year":"2009","unstructured":"Wang, Z., Bovik, A.C.: Mean squared error: love it or leave it? A new look at signal fidelity measures. IEEE Signal Process. Mag. 26, 98\u2013117 (2009)","journal-title":"IEEE Signal Process. Mag."},{"issue":"8","key":"1367_CR12","doi-asserted-by":"crossref","first-page":"1352","DOI":"10.1057\/jors.2014.103","volume":"66","author":"C Tofallis","year":"2015","unstructured":"Tofallis, C.: A better measure of relative prediction accuracy for model selection and model estimation. J. Oper. Res. Soc. 66(8), 1352\u20131362 (2015)","journal-title":"J. Oper. Res. Soc."},{"issue":"10","key":"1367_CR13","doi-asserted-by":"crossref","first-page":"1477","DOI":"10.1109\/83.718487","volume":"7","author":"MA Butt","year":"1998","unstructured":"Butt, M.A., Maragos, P.: Optimum design of chamfer distance transforms. IEEE Trans. Image Process. 7(10), 1477\u20131484 (1998)","journal-title":"IEEE Trans. Image Process."},{"key":"1367_CR14","doi-asserted-by":"publisher","unstructured":"Grevera, G.J.: Distance transform algorithms and their implementation and evaluation. In: Deformable Models , pp. 33\u201360. Springer (2007). doi: 10.1007\/978-0-387-68413-0_2","DOI":"10.1007\/978-0-387-68413-0_2"},{"issue":"9","key":"1367_CR15","doi-asserted-by":"crossref","first-page":"1763","DOI":"10.1109\/TPDS.2012.300","volume":"24","author":"W Liu","year":"2013","unstructured":"Liu, W., Jiang, H., Bai, X., Tan, G., Wang, C., Liu, W., Cai, K.: Distance transform-based skeleton extraction and its applications in sensor networks. IEEE Trans. Parallel Distrib. Syst. 24(9), 1763\u20131772 (2013)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"1367_CR16","doi-asserted-by":"publisher","unstructured":"Xu, D., Li, H., Zhang, Y.: Fast and accurate calculation of protein depth by Euclidean distance transform. In: Research in Computational Molecular Biology, pp. 304\u2013316. Springer (2013). doi: 10.1007\/978-3-642-37195-0_30","DOI":"10.1007\/978-3-642-37195-0_30"},{"key":"1367_CR17","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s11760-012-0419-9","volume":"9","author":"Y Mishchenko","year":"2015","unstructured":"Mishchenko, Y.: A fast algorithm for computation of discrete Euclidean distance transform in three or more dimensions on vector processing architectures. Signal Image Video Process. 9, 19\u201327 (2015)","journal-title":"Signal Image Video Process."},{"key":"1367_CR18","doi-asserted-by":"crossref","unstructured":"Salvi, D., Zheng, K., Zhou, Y., Wang, S.: Distance transform based active contour approach for document image rectification. In: Applications of Computer Vision (WACV), 2015 IEEE Winter Conference on IEEE , pp. 757\u2013764 (2015)","DOI":"10.1109\/WACV.2015.106"},{"key":"1367_CR19","doi-asserted-by":"crossref","first-page":"266","DOI":"10.5772\/56581","volume":"10","author":"JC Elizondo-Leal","year":"2013","unstructured":"Elizondo-Leal, J.C., Parra-Gonz\u00e1lez, E.F., Ram\u00edrez-Torres, J.G.: The exact Euclidean distance transform: a new algorithm for universal path planning. Int. J. Adv. Robot. Syst. 10, 266 (2013)","journal-title":"Int. J. Adv. Robot. Syst."},{"key":"1367_CR20","doi-asserted-by":"publisher","unstructured":"Linn\u00e9r, E., Strand, R.: Anti-aliased Euclidean distance transform on 3D sampling lattices. In: Discrete Geometry for Computer Imagery, pp. 88\u201398. Springer (2014). doi: 10.1007\/978-3-319-09955-2_8","DOI":"10.1007\/978-3-319-09955-2_8"},{"key":"1367_CR21","doi-asserted-by":"crossref","unstructured":"Dong, J., Sun, C., Yang, W.: An improved method for oriented chamfer matching. In: Intelligence Science and Big Data Engineering, pp. 875\u2013879. Springer (2013)","DOI":"10.1007\/978-3-642-42057-3_110"},{"key":"1367_CR22","doi-asserted-by":"crossref","unstructured":"Tzionas, D., Gall, J.: A comparison of directional distances for hand pose estimation. In: Pattern Recognition, pp. 131\u2013141. Springer (2013)","DOI":"10.1007\/978-3-642-40602-7_14"},{"issue":"12","key":"1367_CR23","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1109\/LSP.2013.2283254","volume":"20","author":"P Kaliamoorthi","year":"2013","unstructured":"Kaliamoorthi, P., Kakarala, R.: Directional chamfer matching in 2.5 dimensions. IEEE Signal Process Lett 20(12), 1151\u20131154 (2013)","journal-title":"IEEE Signal Process Lett"},{"key":"1367_CR24","doi-asserted-by":"crossref","unstructured":"Nguyen, D.T.: A novel chamfer template matching method using variational mean field. In: 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2425\u20132432. IEEE (2014)","DOI":"10.1109\/CVPR.2014.311"},{"key":"1367_CR25","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/1049-9652(92)90034-U","volume":"54","author":"DW Paglieroni","year":"1992","unstructured":"Paglieroni, D.W.: Distance transforms: Properties and machine vision applications. CVGIP Graph. Models Image Process. 54, 56\u201374 (1992)","journal-title":"CVGIP Graph. Models Image Process."},{"key":"1367_CR26","doi-asserted-by":"publisher","unstructured":"Ma, T., Yang, X., Latecki, L.J.: Boosting chamfer matching by learning chamfer distance normalization. In: Computer Vision\u2013ECCV 2010, pp. 450\u2013463. Springer (2010). doi: 10.1007\/978-3-642-15555-0_33","DOI":"10.1007\/978-3-642-15555-0_33"},{"key":"1367_CR27","doi-asserted-by":"publisher","unstructured":"Thiel, E., Montanvert, A.: Shape splitting from medial lines using the 3\u20134 chamfer distance. In: Visual Form, pp. 537\u2013546. Springer (1992). doi: 10.1007\/978-1-4899-0715-8_51","DOI":"10.1007\/978-1-4899-0715-8_51"},{"issue":"2","key":"1367_CR28","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1006\/cviu.1999.0783","volume":"76","author":"O Cuisenaire","year":"1999","unstructured":"Cuisenaire, O., Macq, B.: Fast Euclidean distance transformation by propagation using multiple neighborhoods. Comput. Vis. Image Underst. 76(2), 163\u2013172 (1999)","journal-title":"Comput. Vis. Image Underst."},{"issue":"11","key":"1367_CR29","doi-asserted-by":"crossref","first-page":"1551","DOI":"10.1016\/0031-3203(94)90133-3","volume":"27","author":"T Saito","year":"1994","unstructured":"Saito, T., Toriwaki, J.I.: New algorithms for Euclidean distance transformation of an n-dimensional digitized picture with applications. Pattern Recognit. 27(11), 1551\u20131565 (1994)","journal-title":"Pattern Recognit."},{"issue":"2","key":"1367_CR30","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.cviu.2003.09.004","volume":"93","author":"FY Shih","year":"2004","unstructured":"Shih, F.Y., Wu, Y.T.: Fast Euclidean distance transformation in two scans using a 3 $$\\times $$ \u00d7 3 neighborhood. Comput. Vis. Image Underst. 93(2), 195\u2013205 (2004)","journal-title":"Comput. Vis. Image Underst."},{"issue":"11","key":"1367_CR31","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1016\/0167-8655(91)90004-6","volume":"12","author":"BJ Verwer","year":"1991","unstructured":"Verwer, B.J.: Local distances for distance transformations in two and three dimensions. Pattern Recognit. Lett. 12(11), 671\u2013682 (1991)","journal-title":"Pattern Recognit. Lett."},{"key":"1367_CR32","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.neucom.2015.12.114","volume":"192","author":"A Myttenaere De","year":"2016","unstructured":"De Myttenaere, A., Golden, B., Le Grand, B., Rossi, F.: Mean absolute percentage error for regression models. Neurocomputing 192, 38\u201348 (2016)","journal-title":"Neurocomputing"},{"key":"1367_CR33","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.ijforecast.2015.03.008","volume":"32","author":"PH Franses","year":"2016","unstructured":"Franses, P.H.: A note on the mean absolute scaled error. Int. J. Forecast. 32, 20\u201322 (2016)","journal-title":"Int. J. Forecast."},{"key":"1367_CR34","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.apenergy.2015.10.184","volume":"163","author":"M Majidpour","year":"2016","unstructured":"Majidpour, M., Qiu, C., Chu, P., Pota, H.R., Gadh, R.: Forecasting the EV charging load based on customer profile or station measurement? Appl. Energy 163, 134\u2013141 (2016)","journal-title":"Appl. Energy"},{"issue":"11","key":"1367_CR35","doi-asserted-by":"crossref","first-page":"985","DOI":"10.1109\/TSE.2003.1245300","volume":"29","author":"T Foss","year":"2003","unstructured":"Foss, T., Stensrud, E., Kitchenham, B., Myrtveit, I.: A simulation study of the model evaluation criterion MMRE. IEEE Trans. Softw. Eng. 29(11), 985\u2013995 (2003)","journal-title":"IEEE Trans. Softw. Eng."}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00371-017-1367-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-017-1367-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-017-1367-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,23]],"date-time":"2019-09-23T12:38:00Z","timestamp":1569242280000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00371-017-1367-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,6]]},"references-count":35,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2018,5]]}},"alternative-id":["1367"],"URL":"https:\/\/doi.org\/10.1007\/s00371-017-1367-8","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,5,6]]}}}