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Relevant bibliographies by topics / Cursive handwriting

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Academic literature on the topic 'Cursive handwriting'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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Journal articles on the topic "Cursive handwriting"

1

Ziviani, Jenny. "Use of Modern Cursive Handwriting and Handwriting Speed for Children Ages 7 to 14 Years." Perceptual and Motor Skills 82, no. 1 (February 1996): 282. http://dx.doi.org/10.2466/pms.1996.82.1.282.

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Karlsdottir, Ragnheidur. "Development of Cursive Handwriting." Perceptual and Motor Skills 82, no. 2 (April 1996): 659–73. http://dx.doi.org/10.2466/pms.1996.82.2.659.

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The efficiency of two different instructional methods for improving the growth of handwriting quality in the upper grades of primary school was investigated in field experiments using a control-group design. No improvement in mean quality was found for a group of 38 children using a method based on copying exercises. A substantial improvement in mean quality, corresponding to about 1.4 SD, was found for 23 children using a method based on reintroduction of the letter forms explaining each form visually and verbally. It was concluded that the bottleneck in the development of handwriting quality in primary school is a mismatch between the instructional methods used and the perceptual ability of the children.

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Bo, Jin, Julia Barta, Hilary Ferencak, Sara Comstock, Vanessa Riley, and Joni Krueger. "Developmental Characteristics in Cursive and Printed Letter-Writing for School-Age Children." Journal of Motor Learning and Development 2, no. 1 (March 2014): 1–8. http://dx.doi.org/10.1123/jmld.2012-0001.

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The current study evaluated the developmental characteristics of printed and cursive letter writing in early school-age children. We predicted fewer age-related changes on spatial and temporal measures in cursive letter writing due to lower explicit timing demands compared with printed letter writing. Thirty children wrote the letters e and l in cursive and printed forms repetitively. For printed letters, significant age effects were seen in temporal consistency, whereas cursive letters showed age-related improvement in spatial consistency. Children tended to have higher consistency for printed handwriting than they did for cursive writing. Because of an overall advantage for printed handwriting, the explicit timing hypothesis was not fully supported. We argue that experiential factors influence the development of handwriting.

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Huang, Tongcheng, Siyang Zhang, Xu Duan, and Ronglong Liang. "On-Line Handy Handwriting Chinese Characters Input for Non-Chinese Speakers Based on Wavelet Neural Network." International Journal of Pattern Recognition and Artificial Intelligence 30, no. 06 (May 9, 2016): 1659017. http://dx.doi.org/10.1142/s0218001416590175.

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Non-Chinese speakers hold increasing opportunities and need to process Chinese information and communicate in Chinese. This paper, with the purpose of facilitating the handwriting input of Chinese characters for non-Chinese speakers, is directed towards the development of the handwriting rules and vocabulary for Latin-style anti-cursive characters and the ways of their selection and classification. This aims to build a practical platform by utilizing three characteristics of wavelet neural network — automatically ascertaining the number of hidden layer unit, converging rapidly and never running into the partial minimum of networks — for a simple Latin-style online handwriting input and processing, meanwhile, taking the customary handwriting habits of non-Chinese speakers. The paper, based on profound information of cursive characters, deciphered the genetic code of ancient cursive symbols and made clear the rules for characters changing into its cursive style. As a result, it breaks the bottleneck, which enables non-Chinese speakers to easily input information through handwriting Chinese characters.

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Fitrianingsih, Fitrianingsih, Sarifuddin Madenda, Ernastuti Ernastuti, Suryarini Widodo, and Rodiah Rodiah. "Cursive Handwriting Segmentation using Ideal Distance Approach." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 5 (October 1, 2017): 2863. http://dx.doi.org/10.11591/ijece.v7i5.pp2863-2872.

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Offline cursive handwriting becomes a major challenge due to the huge amount of handwriting varieties such as slant handwriting, space between words, the size and direction of the letter, the style of writing the letter and handwriting with contour similarity on some letters. There are some steps for recursive handwriting recognition. The steps are preprocessing, morphology, segmentation, features of letter extraction and recognition. Segmentation is a crucial process in handwriting recognition since the success of segmentation step will determine the success level of recognition. This paper proposes a segmentation algorithm that segment recursive handwriting into letters. These letters will form words using a method that determine the intersection cutting point of image recursive handwriting with an ideal image distance. The ideal distance of recursive handwriting image is an ideal distance segmentation point in order to avoid the cutting of other letter’s section. The width and height of images are used to determine the accurate segmentation point. There were 999 recursive handwriting input images taken from 25 researchers used for this study. The images used are the images obtained from preprocessing step. Those are the images with slope correction. This study used Support Vector Machine (SVM) to recognize recursive handwriting. The experiments show the proposed segmentation algorithm able to segment the image precisely and have 97% success recognizing the recursive handwriting.

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Karlsdottir, Ragnheidur. "Comparison of Cursive Models for Handwriting Instruction." Perceptual and Motor Skills 85, no. 3_suppl (December 1997): 1171–84. http://dx.doi.org/10.2466/pms.1997.85.3f.1171.

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The efficiency of four different cursive handwriting styles as model alphabets for handwriting instruction of primary school children was compared in a cross-sectional field experiment from Grade 3 to 6 in terms of the average handwriting speed developed by the children and the average rate of convergence of the children's handwriting to the style of their model. It was concluded that styles with regular entry stroke patterns give the steadiest rate of convergence to the model and styles with short ascenders and descenders and strokes with not too high curvatures give the highest handwriting speed.

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Zou, Mingfu. "On-Line Handwriting Cursive Recognition." Journal of Computer Research and Development 43, no. 1 (2006): 138. http://dx.doi.org/10.1360/crad20060122.

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Singer, Y., and N. Tishby. "Dynamical encoding of cursive handwriting." Biological Cybernetics 71, no. 3 (August 1, 1994): 227–37. http://dx.doi.org/10.1007/s004220050085.

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Singer, Y., and N. Tishby. "Dynamical encoding of cursive handwriting." Biological Cybernetics 71, no. 3 (July 1994): 227–37. http://dx.doi.org/10.1007/bf00202762.

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Morin, Marie-France, Natalie Lavoie, and Isabelle Montésinos-Gelet. "The Effects of Manuscript, Cursive or Manuscript/Cursive Styles on Writing Development in Grade 2." Language and Literacy 14, no. 1 (January 25, 2012): 110. http://dx.doi.org/10.20360/g21s3v.

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In the research area of writing development, an increasing number of researchers suggest that graphomotor skills could be much more important than they appear to be (Christensen, 2009). Few researchers have studied the link between handwriting and teaching practices, despite the fact that some studies indicate its importance (Graham, 2010). The general objective of this study is to explore the relationship between different handwriting styles and the development of writing skills among 715 children in Grade 2. Generally, our results show that the three handwriting styles (manuscript/cursive, manuscript, and cursive) have different effects on writing development (speed, quality, word production, and text production).

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Dissertations / Theses on the topic "Cursive handwriting"

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Hennig, Andreas. "Recognising a page of unconstrained cursive handwriting." Thesis, Nottingham Trent University, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285727.

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Günter, Simon. "Multiple classifier systems in offline cursive handwriting recognition." [S.l.] : [s.n.], 2004. http://www.stub.unibe.ch/download/eldiss/04guenter_s.pdf.

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Varga, Tamás. "Off-line cursive handwriting recognition using synthetic training data." Berlin Aka, 2006. http://deposit.d-nb.de/cgi-bin/dokserv?id=2838183&prov=M&dok_var=1&dok_ext=htm.

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Senior, Andrew William. "Off-line cursive handwriting recognition using recurrent neural networks." Thesis, University of Cambridge, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338024.

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Bristow, Kelly H. "Freeform Cursive Handwriting Recognition Using a Clustered Neural Network." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804845/.

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Optical character recognition (OCR) software has advanced greatly in recent years. Machine-printed text can be scanned and converted to searchable text with word accuracy rates around 98%. Reasonably neat hand-printed text can be recognized with about 85% word accuracy. However, cursive handwriting still remains a challenge, with state-of-the-art performance still around 75%. Algorithms based on hidden Markov models have been only moderately successful, while recurrent neural networks have delivered the best results to date. This thesis explored the feasibility of using a special type of feedforward neural network to convert freeform cursive handwriting to searchable text. The hidden nodes in this network were grouped into clusters, with each cluster being trained to recognize a unique character bigram. The network was trained on writing samples that were pre-segmented and annotated. Post-processing was facilitated in part by using the network to identify overlapping bigrams that were then linked together to form words and sentences. With dictionary assisted post-processing, the network achieved word accuracy of 66.5% on a small, proprietary corpus. The contributions in this thesis are threefold: 1) the novel clustered architecture of the feed-forward neural network, 2) the development of an expanded set of observers combining image masks, modifiers, and feature characterizations, and 3) the use of overlapping bigrams as the textual working unit to assist in context analysis and reconstruction.

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Powalka, Robert Kazimierz. "An algorithm toolbox for on-line cursive script recognition." Thesis, Nottingham Trent University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283031.

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Wong, Wing Seong. "Form analysis using colour and context." Thesis, Nottingham Trent University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366081.

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Karlsson, Elsa. "The Story of Handwriting : Is handwriting as a practice still used in Swedish schools?" Thesis, Linnéuniversitetet, Institutionen för design (DE), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-77136.

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This design project will map, look at and give answers regarding: The story of handwriting from a pedagogical perspective, within a Swedish context. It is primarily based on a great interest in writing by hand, and the effects and benefits it has on its practitioners. Handwriting today compared to before is getting less space in the digitized society, but is handwriting as a practice still used in Swedish schools? The predicted meaning is that children in school cannot write properly by hand anymore, due to all technologies such as smartphones, tablets and computers. The question is complex and the answer is more than just a simple yes or no, and therefore this investigation in handwriting has been done. The thesis will look back in the history of handwriting and give answers to the question through both theory and practice. Through research it will document differences and similarities between how people born between 1930-1959 and today’s lower elementary school children are looking at and working with handwriting. To be able to make this comparison—a digital survey, field studies, workshops and handwritten letters and notes from persons within the two defined research groups has worked as research methods to make the result as reliable as possible. Until recently, the art of writing more known as “Välskrivning” was a very central competence in Swedish school. It was a graded subject where focus was on how to write properly and practice good handwriting. The fact that “Välskrivning” is no longer a school subject means that the children today do not have the same prerequisites for succeeding with handwriting in the long term. They get other opportunities in the digital world, but one does not have to exclude the other. In my research I have found that despite technological tools and advancements, children still enjoy and value writing by hand, and then it is my task as a change agent to break the norm that handwriting as a practice is disappearing in Swedish schools and give children the tools they need to continue writing new chapters in the story of handwriting. To stimulate learning with joy, work with fine motor skills and strengthen the ability to concentrate amongst children through a handwriting workshop is what the investigation has led to. The answers in this thesis will not change the world, but the handwriting workshop, designed as a pedagogical tool, will hopefully inspire and motivate children to write by hand for a long time to come.

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Dumont, Danièle. "Le système d’écriture des minuscules latines manuscrites en usage dans les écoles françaises : intérêt de la prise en compte de ce système pour l’enseignement de l’écriture manuscrite." Thesis, Paris 5, 2013. http://www.theses.fr/2013PA05H004/document.

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Notre démarche repose sur le constat que de plus en plus d’enfants sont en difficulté d’écriture. Elle vise à proposer une base de réflexion sur laquelle pourrait s’appuyer un enseignement structuré de l’écriture. Notre recherche porte sur l’écriture des lettres minuscules cursives manuscrites latines en usage dans les écoles françaises. Nous avons fait l’hypothèse que cette écriture, produit de l’école française, constitue un système dont nous pouvons désigner les éléments et définir le fonctionnement. Cette hypothèse ouvre sur la perspective que la prise en compte de ce système pourrait être une aide à l’apprentissage de l’écriture. Notre choix est conforté par les résultats des neurosciences qui montrent qu’écrire à la main serait une aide à l’apprentissage de la lecture. A partir de l’analyse de commentaires sur la lisibilité d’un corpus d’écritures manuscrites, nous montrerons comment est construit ce système et quelles relations hiérarchiques et fonctionnelles ses éléments entretiennent entre eux. Nous y verrons que le cœur du système s’organiserait en deux unités minimales, déclinées chacune en une forme de base et deux dérivées pour l’une, trois dérivées pour l’autre. Le système constitué par l’ensemble de ces sept formes permettrait d’écrire toutes les lettres minuscules cursives latines en usage en France.En ouverture vers d’autres projets, nous avons mis ce système à l’épreuve de la reconnaissance des lettres par des enfants d’école maternelle. Nous avons constaté une amélioration du score entre avant et après une séance d’observation commentée collective. Cette recherche sur le système d’écriture des lettres minuscules cursives latines nous a conduite à avancer des propositions pédagogiques pour l’enseignement de l’écriture
Our processes are based on the fact that more and more children have difficulties with handwriting. Its aim is to propose a basis for thought on which a structured teaching of handwriting could lean. Our research focuses on Latin handwritten cursive small letters used in French schools. We made the assumption that this writing - a French school product - constitutes a system, the elements of which can be named and the functioning described. This hypothesis leads to the viewpoint that to take this system into account could be a help in the teaching of writing. Our choice is backed up by the results of neurosciences which show that to write with the hand would be a help in learning to read. From the analysis of comments on the legibility of a corpus of handwritings, we shall show how this system is built and what hierarchic and functional relations its elements continuously use with each other. We shall see that the heart of the system would be organized into two minimal units. Each of them set up as a basic form and two derivatives for the one, three for the other. The system constituted by these seven forms would allow all of the Latin cursive small letters used in France to be written. As an opening towards others projects, we submitted this system to the recognition of letters by children at nursery school. We noticed an improvement of the score between before and after a session of collective commented observation of the letters. This research about Latin handwritten cursive small letters brought us to make certain pedagogical proposals for the training of teachers

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Evans, Anthoinette. "The effects of training, self-recording, and public charting on the cursive handwriting legibility of intermediate developmentally handicapped children." The Ohio State University, 1985. http://rave.ohiolink.edu/etdc/view?acc_num=osu1314731794.

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Books on the topic "Cursive handwriting"

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Cummings, Renee. Handwriting: Traditional cursive. Grand Rapids, MI: Instructional Fair, 1992.

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Cummings, Renee. Handwriting: Traditional cursive. Grand Rapids, MI: Instructional Fair, 1992.

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Handwriting: Cursive. Grades 3-5. Greensboro, NC: Carson-Dellosa Publishing, 2006.

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Letterland full cursive: Handwriting stagethree. Cambridge: Letterland, 1993.

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Bertin, Phyllis. Handwriting program for cursive: Right handed. Cambridge, MA: Educators Publishing Service, 1997.

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Bertin, Phyllis. Handwriting program for cursive: Left handed. Cambridge, MA: Educators Publishing Service, 1997.

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ill, Gordon Mike, ed. Stacey Coolidge's fancy-smancy cursive handwriting. San Francisco, CA: Little Pickle Press, 2018.

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Bertin, Phyllis. Handwriting program for cursive: Right handed. Cambridge, MA: Educators Publishing Service, 1997.

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Bertin, Phyllis. Handwriting program for cursive: Left handed. Cambridge, MA: Educators Publishing Service, 1997.

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Wendon, Lyn. Letterland towards cursive: Handwriting stage two. Cambridge: Letterland, 1993.

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Book chapters on the topic "Cursive handwriting"

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Lecolinet, Eric, and Olivier Baret. "Cursive Word Recognition: Methods and Strategies." In Fundamentals in Handwriting Recognition, 235–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-78646-4_14.

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Cheriet, Mohamed. "Towards a Visual Recognition of Cursive Script." In Fundamentals in Handwriting Recognition, 223–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-78646-4_12.

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Teulings, Hans-Leo. "Invariant Handwriting Features Useful in Cursive-Script Recognition." In Fundamentals in Handwriting Recognition, 179–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-78646-4_9.

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Bunke, Horst, and Tamás Varga. "Off-Line Roman Cursive Handwriting Recognition." In Digital Document Processing, 165–83. London: Springer London, 2007. http://dx.doi.org/10.1007/978-1-84628-726-8_8.

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Fischer, Andreas, and Horst Bunke. "Kernel PCA for HMM-Based Cursive Handwriting Recognition." In Computer Analysis of Images and Patterns, 181–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03767-2_22.

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Dhande, Pritam S., and Reena Kharat. "Study of Segmentation Techniques for Cursive English Handwriting Recognition." In Advances in Intelligent Systems and Computing, 567–76. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5520-1_51.

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Ibrahim, Mayire, Heng Zhang, Cheng-Lin Liu, and Askar Hamdulla. "An Effective Character Separation Method for Online Cursive Uyghur Handwriting." In Communications in Computer and Information Science, 530–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33506-8_65.

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Comajuncosas, Andreu, Marcos Faundez-Zanuy, Jordi Solé-Casals, and Marta Portero-Tresserra. "Preliminary Study on Implications of Cursive Handwriting Learning in Schools." In Multidisciplinary Approaches to Neural Computing, 339–44. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56904-8_32.

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Bezerra, Byron Leite Dantas, Cleber Zanchettin, and Vinícius Braga de Andrade. "A MDRNN-SVM Hybrid Model for Cursive Offline Handwriting Recognition." In Artificial Neural Networks and Machine Learning – ICANN 2012, 246–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33266-1_31.

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Helmers, Muriel, and Horst Bunke. "Generation and Use of Synthetic Training Data in Cursive Handwriting Recognition." In Pattern Recognition and Image Analysis, 336–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-44871-6_39.

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Conference papers on the topic "Cursive handwriting"

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Stefano, Claudio De, Angelo Marcelli, Antonio Parziale, and Rosa Senatore. "Reading Cursive Handwriting." In 2010 International Conference on Frontiers in Handwriting Recognition (ICFHR). IEEE, 2010. http://dx.doi.org/10.1109/icfhr.2010.21.

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Kamel, Ibrahim. "Fast retrieval of cursive handwriting." In the fifth international conference. New York, New York, USA: ACM Press, 1996. http://dx.doi.org/10.1145/238355.238447.

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Yanikoglu and Sandon. "Recognizing off-line cursive handwriting." In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. IEEE Comput. Soc. Press, 1994. http://dx.doi.org/10.1109/cvpr.1994.323857.

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Choudhary, Umesh, Sampada Bhosale, Sonali Bhise, and Purushottam Chilveri. "A survey: Cursive handwriting recognition techniques." In 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT). IEEE, 2017. http://dx.doi.org/10.1109/rteict.2017.8256892.

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Morasso. "Neural models of cursive script handwriting." In International Joint Conference on Neural Networks. IEEE, 1989. http://dx.doi.org/10.1109/ijcnn.1989.118295.

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Schambach, Marc-Peter. "Recurrent HMMs and Cursive Handwriting Recognition Graphs." In 2009 10th International Conference on Document Analysis and Recognition. IEEE, 2009. http://dx.doi.org/10.1109/icdar.2009.217.

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Gatos, B., I. Pratikakis, and S. J. Perantonis. "Hybrid Off-Line Cursive Handwriting Word Recognition." In 18th International Conference on Pattern Recognition (ICPR'06). IEEE, 2006. http://dx.doi.org/10.1109/icpr.2006.644.

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Fajardo, Lovely Joy, Nino Joshua Sorillo, Jaycel Garlit, Cia Dennise Tomines, Mideth B. Abisado, Joseph Marvin R. Imperial, Ramon L. Rodriguez, and Bernie S. Fabito. "Doctor’s Cursive Handwriting Recognition System Using Deep Learning." In 2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM ). IEEE, 2019. http://dx.doi.org/10.1109/hnicem48295.2019.9073521.

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Yanikoglu, Berrin A., and Peter A. Sandon. "Off-line cursive handwriting recognition using neural networks." In Optical Engineering and Photonics in Aerospace Sensing, edited by Steven K. Rogers. SPIE, 1993. http://dx.doi.org/10.1117/12.152559.

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Miyata, Shinya, and Hiroyuki Fujioka. "Design of cursive handwriting characters using esthetic evaluation." In 2010 International Conference on Control, Automation and Systems (ICCAS 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccas.2010.5670186.

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