{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T14:08:33Z","timestamp":1762956513486},"reference-count":39,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. & Syst."],"published-print":{"date-parts":[[2020,12,1]]},"DOI":"10.1587\/transinf.2020edp7099","type":"journal-article","created":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T22:19:47Z","timestamp":1606774787000},"page":"2701-2708","source":"Crossref","is-referenced-by-count":7,"title":["Online Signature Verification Using Single-Template Matching Through Locally and Globally Weighted Dynamic Time Warping"],"prefix":"10.1587","volume":"E103.D","author":[{"given":"Manabu","family":"OKAWA","sequence":"first","affiliation":[{"name":"Forensic Science Laboratory, Metropolitan Police Department"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"publisher","unstructured":"[1] R. Plamondon, G. Pirlo, E. Anquetil, C. R\u00e9mi, H.-L. Teulings, and M. Nakagawa, \u201cPersonal digital bodyguards for e-security, e-learning and e-health: A prospective survey,\u201d Pattern Recognit., vol.81, pp.633-659, 2018. 10.1016\/j.patcog.2018.04.012","DOI":"10.1016\/j.patcog.2018.04.012"},{"key":"2","doi-asserted-by":"publisher","unstructured":"[2] M. Diaz, M.A. Ferrer, D. Impedovo, M.I. Malik, G. Pirlo, and R. Plamondon, \u201cA perspective analysis of handwritten signature technology,\u201d ACM Computing Surveys (CSUR), vol.51, no.6, pp.117:1-117:39, 2019. 10.1145\/3274658","DOI":"10.1145\/3274658"},{"key":"3","doi-asserted-by":"publisher","unstructured":"[3] M. Okawa and K. Yoshida, \u201cOffline writer verification based on forensic expertise: Analyzing multiple characters by combining the shape and advanced pen pressure information,\u201d Jpn. J. Forensic Sci. Tech., vol.22, no.2, pp.61-75, 2017. 10.3408\/jafst.731","DOI":"10.3408\/jafst.731"},{"key":"4","doi-asserted-by":"publisher","unstructured":"[4] J. Linden, R. Marquis, S. Bozza, and F. Taroni, \u201cDynamic signatures: A review of dynamic feature variation and forensic methodology,\u201d Forensic Sci Int., vol.291, pp.216-229, 2018. 10.1016\/j.forsciint.2018.08.021","DOI":"10.1016\/j.forsciint.2018.08.021"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] L. Mohammed, Forensic Examination of Signatures, 1st ed., Academic Press, 2019.","DOI":"10.1016\/B978-0-12-813029-2.00001-3"},{"key":"6","doi-asserted-by":"publisher","unstructured":"[6] M. Okawa and K. Yoshida, \u201cOffline writer verification using pen pressure information from infrared image,\u201d IET Biometrics, vol.2, no.4, pp.199-207, 2013. 10.1049\/iet-bmt.2012.0068","DOI":"10.1049\/iet-bmt.2012.0068"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] M. Okawa and K. Yoshida, \u201cText and user generic model for writer verification using combined pen pressure information from ink intensity and indented writing on paper,\u201d IEEE Trans. Human-Mach. Syst., vol.45, no.3, pp.339-349, 2015. 10.1109\/thms.2014.2380828","DOI":"10.1109\/THMS.2014.2380828"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] M. Okawa, \u201cFrom BoVW to VLAD with KAZE features: Offline signature verification considering cognitive processes of forensic experts,\u201d Pattern Recognit. Lett., vol.113, pp.75-82, 2018. 10.1016\/j.patrec.2018.05.019","DOI":"10.1016\/j.patrec.2018.05.019"},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] M. Okawa, \u201cSynergy of foreground-background images for feature extraction: Offline signature verification using Fisher vector with fused KAZE features,\u201d Pattern Recognit., vol.79, pp.480-489, 2018. 10.1016\/j.patcog.2018.02.027","DOI":"10.1016\/j.patcog.2018.02.027"},{"key":"10","doi-asserted-by":"publisher","unstructured":"[10] N. Sae-Bae and N. Memon, \u201cOnline signature verification on mobile devices,\u201d IEEE Trans. Inf. Forensics Security, vol.9, no.6, pp.933-947, 2014. 10.1109\/tifs.2014.2316472","DOI":"10.1109\/TIFS.2014.2316472"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] Y. Liu, Z. Yang, and L. Yang, \u201cOnline signature verification based on DCT and sparse representation,\u201d IEEE Trans. Cybern., vol.45, no.11, pp.2498-2511, 2015. 10.1109\/tcyb.2014.2375959","DOI":"10.1109\/TCYB.2014.2375959"},{"key":"12","doi-asserted-by":"publisher","unstructured":"[12] J. Fierrez, J. Ortega-Garcia, D. Ramos, and J. Gonzalez-Rodriguez, \u201cHMM-based on-line signature verification: Feature extraction and signature modeling,\u201d Pattern Recognit. Lett., vol.28, no.16, pp.2325-2334, 2007. 10.1016\/j.patrec.2007.07.012","DOI":"10.1016\/j.patrec.2007.07.012"},{"key":"13","doi-asserted-by":"publisher","unstructured":"[13] G. Pirlo, V. Cuccovillo, M. Diaz-Cabrera, D. Impedovo, and P. Mignone, \u201cMultidomain verification of dynamic signatures using local stability analysis,\u201d IEEE Trans. Human-Mach. Syst., vol.45, no.6, pp.805-810, 2015. 10.1109\/thms.2015.2443050","DOI":"10.1109\/THMS.2015.2443050"},{"key":"14","doi-asserted-by":"publisher","unstructured":"[14] L. Tang, W. Kang, and Y. Fang, \u201cInformation divergence-based matching strategy for online signature verification,\u201d IEEE Trans. Inf. Forensics Security, vol.13, no.4, pp.861-873, 2018. 10.1109\/tifs.2017.2769023","DOI":"10.1109\/TIFS.2017.2769023"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] M. Okawa, \u201cA single-template strategy using multi-distance measures and weighting for signature verification,\u201d Proc. 18th IEEE Int. Symp. Signal Processing and Information Technology (ISSPIT 2018), pp.46-51, 2018. 10.1109\/isspit.2018.8642687","DOI":"10.1109\/ISSPIT.2018.8642687"},{"key":"16","doi-asserted-by":"crossref","unstructured":"[16] M. Okawa, \u201cOnline signature verification using multi-distance measures and weighting with gradient boosting,\u201d Proc. 1st IEEE Global Conf. Life Sci. and Technologies (LifeTech 2019), pp.277-278, 2019. 10.1109\/lifetech.2019.8884008","DOI":"10.1109\/LifeTech.2019.8884008"},{"key":"17","doi-asserted-by":"publisher","unstructured":"[17] M. Okawa, \u201cTemplate matching using time-series averaging and DTW with dependent warping for online signature verification,\u201d IEEE Access, vol.7, pp.81010-81019, 2019. 10.1109\/access.2019.2923093","DOI":"10.1109\/ACCESS.2019.2923093"},{"key":"18","doi-asserted-by":"publisher","unstructured":"[18] M. Okawa, \u201cOnline signature verification using single-template matching with time-series averaging and gradient boosting,\u201d Pattern Recognit., vol.102, p.107227, 2020. 10.1016\/j.patcog.2020.107227","DOI":"10.1016\/j.patcog.2020.107227"},{"key":"19","doi-asserted-by":"publisher","unstructured":"[19] H. Sakoe and S. Chiba, \u201cDynamic programming algorithm optimization for spoken word recognition,\u201d IEEE Trans. Acoust., Speech, Signal Process., vol.26, no.1, pp.43-49, 1978. 10.1109\/tassp.1978.1163055","DOI":"10.1109\/TASSP.1978.1163055"},{"key":"20","doi-asserted-by":"crossref","unstructured":"[20] M. Okawa, \u201cOnline signature verification using a single-template strategy with mean templates and local stability-weighted dynamic time warping,\u201d Proc. 11th IEEE Int. Workshop Comput. Intell. Appl. (IWCIA 2019), pp.83-88, 2019. 10.1109\/iwcia47330.2019.8955083","DOI":"10.1109\/IWCIA47330.2019.8955083"},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] M. Okawa, \u201cAnalysis of session variability for online signature verification using local stability-weighted DTW,\u201d Proc. 9th IEEE Global Conf. Consumer Electronics (GCCE 2020), pp.295-296, 2020.","DOI":"10.1109\/GCCE50665.2020.9292068"},{"key":"22","doi-asserted-by":"publisher","unstructured":"[22] J.M. Pascual-Gaspar, V. Carde\u00f1oso-Payo, and C. Vivaracho-Pascual, \u201cPractical on-line signature verification,\u201d Advances in Biometrics (Proc. ICB 2009), LNCS 5558, pp.1180-1189, 2009. 10.1007\/978-3-642-01793-3_119","DOI":"10.1007\/978-3-642-01793-3_119"},{"key":"23","doi-asserted-by":"publisher","unstructured":"[23] X. Xia, X. Song, F. Luan, J. Zheng, Z. Chen, and X. Ma, \u201cDiscriminative feature selection for on-line signature verification,\u201d Pattern Recognit., vol.74, pp.422-433, 2018. 10.1016\/j.patcog.2017.09.033","DOI":"10.1016\/j.patcog.2017.09.033"},{"key":"24","doi-asserted-by":"publisher","unstructured":"[24] M. Shokoohi-Yekta, B. Hu, H. Jin, J. Wang, and E. Keogh, \u201cGeneralizing DTW to the multi-dimensional case requires an adaptive approach,\u201d Data Min. Knowl. Disc., vol.31, no.1, pp.1-31, 2017. 10.1007\/s10618-016-0455-0","DOI":"10.1007\/s10618-016-0455-0"},{"key":"25","doi-asserted-by":"publisher","unstructured":"[25] F. Petitjean, A. Ketterlin, and P. Gan\u00e7arski, \u201cA global averaging method for dynamic time warping, with applications to clustering,\u201d Pattern Recognit., vol.44, no.3, pp.678-693, 2011. 10.1016\/j.patcog.2010.09.013","DOI":"10.1016\/j.patcog.2010.09.013"},{"key":"26","doi-asserted-by":"publisher","unstructured":"[26] J.H. Friedman, \u201cGreedy function approximation: A gradient boosting machine,\u201d Annals of statistics, vol.29, no.5, pp.1189-1232, 2001. 10.1214\/aos\/1013203451","DOI":"10.1214\/aos\/1013203451"},{"key":"27","doi-asserted-by":"crossref","unstructured":"[27] D.-Y. Yeung, H. Chang, Y. Xiong, S. George, R. Kashi, T.Matsumoto, and G. Rigoll, \u201cSVC2004: First international signature verification competition,\u201d Biometric Authentication (Proc. ICBA 2004), LNCS 3072, pp.16-22, 2004. 10.1007\/978-3-540-25948-0_3","DOI":"10.1007\/978-3-540-25948-0_3"},{"key":"28","doi-asserted-by":"publisher","unstructured":"[28] J. Ortega-Garcia, J. Fierrez-Aguilar, D. Simon, J. Gonzalez, M. Faundez-Zanuy, V. Espinosa, A. Satue, I. Hernaez, J.-J. Igarza, C. Vivaracho, D. Escudero, and Q.-I. Moro, \u201cMCYT baseline corpus: A bimodal biometric database,\u201d IEE Proceedings-Vision, Image and Signal Processing, vol.150, no.6, pp.395-401, 2003. 10.1049\/ip-vis:20031078","DOI":"10.1049\/ip-vis:20031078"},{"key":"29","doi-asserted-by":"publisher","unstructured":"[29] C. Gruber, T. Gruber, S. Krinninger, and B. Sick, \u201cOnline signature verification with support vector machines based on LCSS kernel functions,\u201d IEEE Trans. Syst. Man, Cybern. B, Cybern., vol.40, no.4, pp.1088-1100, 2010. 10.1109\/tsmcb.2009.2034382","DOI":"10.1109\/TSMCB.2009.2034382"},{"key":"30","doi-asserted-by":"publisher","unstructured":"[30] B.L. Van, S. Garcia-Salicetti, and B. Dorizzi, \u201cOn using the viterbi path along with HMM likelihood information for online signature verification,\u201d IEEE Trans. Syst. Man, Cybern. B, Cybern., vol.37, no.5, pp.1237-1247, 2007. 10.1109\/tsmcb.2007.895323","DOI":"10.1109\/TSMCB.2007.895323"},{"key":"31","doi-asserted-by":"publisher","unstructured":"[31] A. Sharma and S. Sundaram, \u201cAn enhanced contextual DTW based system for online signature verification using vector quantization,\u201d Pattern Recognit. Lett., vol.84, pp.22-28, 2016. 10.1016\/j.patrec.2016.07.015","DOI":"10.1016\/j.patrec.2016.07.015"},{"key":"32","doi-asserted-by":"publisher","unstructured":"[32] S. Lai, L. Jin, L. Lin, Y. Zhu, and H. Mao, \u201cSynSig2Vec: Learning representations from synthetic dynamic signatures for real-world verification,\u201d Proc. 34th AAAI Conf. Artificial Intelligence (AAAI-20), 2020. 10.1609\/aaai.v34i01.5416","DOI":"10.1609\/aaai.v34i01.5416"},{"key":"33","doi-asserted-by":"publisher","unstructured":"[33] A. Sharma and S. Sundaram, \u201cOn the exploration of information from the DTW cost matrix for online signature verification,\u201d IEEE Trans. Cybern., vol.48, no.2, pp.611-624, 2018. 10.1109\/tcyb.2017.2647826","DOI":"10.1109\/TCYB.2017.2647826"},{"key":"34","doi-asserted-by":"publisher","unstructured":"[34] Y. Jia, L. Huang, and H. Chen, \u201cA two-stage method for online signature verification using shape contexts and function features,\u201d Sensors, vol.19, no.8, p.1808, 2019. 10.3390\/s19081808","DOI":"10.3390\/s19081808"},{"key":"35","doi-asserted-by":"crossref","unstructured":"[35] N. Liu and Y. Wang, \u201cTemplate selection for on-line signature verification,\u201d Proc. 19th Int. Conf. Pattern Recognit. (ICPR 2008), pp.1-4, 2008. 10.1109\/icpr.2008.4761537","DOI":"10.1109\/ICPR.2008.4761537"},{"key":"36","doi-asserted-by":"publisher","unstructured":"[36] K. Cpa\u0142ka, M. Zalasi\u0144ski, and L. Rutkowski, \u201cA new algorithm for identity verification based on the analysis of a handwritten dynamic signature,\u201d Appl. Soft Comput., vol.43, pp.47-56, 2016. 10.1016\/j.asoc.2016.02.017","DOI":"10.1016\/j.asoc.2016.02.017"},{"key":"37","doi-asserted-by":"publisher","unstructured":"[37] Z. Xia, T. Shi, N.N. Xiong, X. Sun, and B. Jeon, \u201cA privacy-preserving handwritten signature verification method using combinational features and secure kNN,\u201d IEEE Access, vol.6, pp.46695-46705, 2018. 10.1109\/access.2018.2866411","DOI":"10.1109\/ACCESS.2018.2866411"},{"key":"38","doi-asserted-by":"publisher","unstructured":"[38] D. Guru, K. Manjunatha, S. Manjunath, and M. Somashekara, \u201cInterval valued symbolic representation of writer dependent features for online signature verification,\u201d Expert Syst. Appl., vol.80, pp.232-243, 2017. 10.1016\/j.eswa.2017.03.024","DOI":"10.1016\/j.eswa.2017.03.024"},{"key":"39","unstructured":"[39] M. Okawa, \u201cPushing the limits of online signature verification in the digital age,\u201d INTERPOL Digital 4N6 Pulse, March 2020."}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E103.D\/12\/E103.D_2020EDP7099\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,16]],"date-time":"2021-04-16T00:26:43Z","timestamp":1618532803000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E103.D\/12\/E103.D_2020EDP7099\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,1]]},"references-count":39,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2020]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2020edp7099","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12,1]]}}}