{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T21:20:16Z","timestamp":1777584016999,"version":"3.51.4"},"reference-count":13,"publisher":"Walter de Gruyter GmbH","issue":"3","license":[{"start":{"date-parts":[[2021,5,29]],"date-time":"2021-05-29T00:00:00Z","timestamp":1622246400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Handwritten text recognition systems interpret the scanned script images as text composed of letters. In this paper, efficient offline methods using fuzzy degrees, as well as interval fuzzy degrees of type-2, are proposed to recognize letters beforehand decomposed into strokes. For such strokes, the first stage methods are used to create a set of hypotheses as to whether a group of strokes matches letter or digit patterns. Subsequently, the second-stage methods are employed to select the most promising set of hypotheses with the use of fuzzy degrees. In a primary version of the second-stage system, standard fuzzy memberships are used to measure compatibility between strokes and character patterns. As an extension of the system thus created, interval type-2 fuzzy degrees are employed to perform a selection of hypotheses that fit multiple handwriting typefaces.<\/jats:p>","DOI":"10.2478\/jaiscr-2021-0014","type":"journal-article","created":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T22:30:14Z","timestamp":1622586614000},"page":"229-242","source":"Crossref","is-referenced-by-count":6,"title":["Handwritten Word Recognition Using Fuzzy Matching Degrees"],"prefix":"10.2478","volume":"11","author":[{"given":"Micha\u0142","family":"Wr\u00f3bel","sequence":"first","affiliation":[{"name":"Department of Computational Intelligence , Czestochowa University of Technology , al. Armii Krajowej 36, 42-200 Cz\u0119stochowa , Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Janusz T.","family":"Starczewski","sequence":"additional","affiliation":[{"name":"Department of Computational Intelligence , Czestochowa University of Technology , al. Armii Krajowej 36, 42-200 Cz\u0119stochowa , Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Justyna","family":"Fija\u0142kowska","sequence":"additional","affiliation":[{"name":"Management Department , University of Social Sciences , 90-113 \u0141od\u017a"},{"name":"Clark University Worcester , MA 01610, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Agnieszka","family":"Siwocha","sequence":"additional","affiliation":[{"name":"Information Technology Institute , University of Social Sciences , 90-113 \u0141od\u017a"},{"name":"Clark University Worcester , MA 01610, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christian","family":"Napoli","sequence":"additional","affiliation":[{"name":"Department of Computer, Control and Management Engineering , Sapienza University of Rome , Via Ariosto 25 Roma 00185 , Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2021,5,29]]},"reference":[{"key":"2026042814152398641_j_jaiscr-2021-0014_ref_001","unstructured":"[1] D. Dubois and H. Prade. Fuzzy sets and systems: Theory and applications. Academic Press, Inc., New York, 1980."},{"key":"2026042814152398641_j_jaiscr-2021-0014_ref_002","doi-asserted-by":"crossref","unstructured":"[2] M. Jones and D. Mewhort. Case-sensitive letter and bigram frequency counts from large-scale english corpora. Behavior Research Methods, Instruments, & Computers, 36:388\u2013396, 2004.10.3758\/BF03195586","DOI":"10.3758\/BF03195586"},{"key":"2026042814152398641_j_jaiscr-2021-0014_ref_003","doi-asserted-by":"crossref","unstructured":"[3] E. L\u2019Homer. Extraction of strokes in handwritten characters. Pattern Recognition, 33:1147\u20131160, 2000.10.1016\/S0031-3203(99)00103-X","DOI":"10.1016\/S0031-3203(99)00103-X"},{"key":"2026042814152398641_j_jaiscr-2021-0014_ref_004","doi-asserted-by":"crossref","unstructured":"[4] J. M. Mendel. Computing with words and its relationships with fuzzistics. Information Sciences, 177(4):988\u20131006, 2007.10.1016\/j.ins.2006.06.008","DOI":"10.1016\/j.ins.2006.06.008"},{"key":"2026042814152398641_j_jaiscr-2021-0014_ref_005","doi-asserted-by":"crossref","unstructured":"[5] R. K. Nowicki and J. T. Starczewski. A new method for classification of imprecise data using fuzzy rough fuzzification. Inf. Sci., 414:33\u201352, 2017.10.1016\/j.ins.2017.05.049","DOI":"10.1016\/j.ins.2017.05.049"},{"key":"2026042814152398641_j_jaiscr-2021-0014_ref_006","doi-asserted-by":"crossref","unstructured":"[6] D. J. Ostrowski and P. Y. K. Cheung. A Fuzzy Logic Approach to Handwriting Recognition, pages 299\u2013314. Vieweg+Teubner Verlag, Wiesbaden, 1996.10.1007\/978-3-322-88955-3_10","DOI":"10.1007\/978-3-322-88955-3_10"},{"key":"2026042814152398641_j_jaiscr-2021-0014_ref_007","doi-asserted-by":"crossref","unstructured":"[7] D. Phan, I.-S. Na, S.-H. Kim, G.-S. Lee, and H.-J. Yang. Triangulation based skeletonization and trajectory recovery for handwritten character patterns. KSII Transactions on Internet and Information Systems, 9:358\u2013377, 2015.10.3837\/tiis.2015.01.022","DOI":"10.3837\/tiis.2015.01.022"},{"key":"2026042814152398641_j_jaiscr-2021-0014_ref_008","doi-asserted-by":"crossref","unstructured":"[8] J. T. Starczewski. Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty, volume 284 of Studies in Fuzziness and Soft Computing. Springer, 2013.10.1007\/978-3-642-29520-1","DOI":"10.1007\/978-3-642-29520-1"},{"key":"2026042814152398641_j_jaiscr-2021-0014_ref_009","doi-asserted-by":"crossref","unstructured":"[9] M. Wr\u00f3bel, K. Nieszporek, J. T. Starczewski, and A. Cader. A fuzzy measure for recognition of handwritten letter strokes. In L. Rutkowski, R. Scherer, M. Korytkowski, W. Pedrycz, R. Tadeusiewicz, and J. M. Zurada, editors, Artificial Intelligence and Soft Computing, pages 761\u2013770, Cham, 2018. 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