• Journal of The Korean Association of Information Education
• /
• v.4 no.2
• /
• pp.129-139
• /
• 2001

For the efficient teaching of Korean characters(Hangul) handwriting method, it needs to the collection of Hangul handwriting samples and the study of analysis methods. For the collection of Hangul handwriting samples, the students of teacher's university take part in this survey. The analysis is performed according to the characters and graphemes in Hangul. The analysis features include the number of strokes, the direction of handwriting, the relational position of graphemes, the height and width of characters, and so on. The results of this analysis will be used for the reference data for the teaching of Hangul handwritings, the study of Hangul fonts, and the research of Hangul information engineering.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.7
• /
• pp.25-32
• /
• 2009

In this paper, we propose a new handwriting verification method using pattern analysis in off-line environments. The proposed method first segments character regions in a document and extracts effective features from the segmented regions. It then estimates the similarity between the extracted non-linear features and reference ones by using dynamic time warping and principal component analysis. Our handwriting verification method extracts handwriting features effectively and enables the verification of handwriting with various lengths of features as well as ones of short patterns. The experimental results show that our method outperforms others in terms as accuracy. We expect that the proposed method will automate the manual handwriting verification tasks and provide much objectivity on handwriting identification.

• Journal of The Korean Society of Integrative Medicine
• /
• v.12 no.1
• /
• pp.183-190
• /
• 2024

Purpose : This study aims to conduct a comprehensive comparison and analysis of intervention strategies utilized for school-aged children facing difficulties in writing, focusing on evaluating the effectiveness of various intervention approaches both domestically and internationally. The primary focus is on assessing the efficacy of each intervention approach and identifying gaps in the existing literature. Methods : Data for this study were gathered from the domestic database RISS from January 2013 to March 2020, and international databases Pubmed and Google Scholar were utilized. The keywords for domestic literature search included 'occupational therapy', 'handwriting', and 'school-aged', while for international literature search, the keywords were 'occupational therapy', 'handwriting', and 'children'. A total of 4 international and 2 domestic articles were selected for review based on predetermined inclusion and exclusion criteria. Results : The study findings present a thorough comparative analysis of intervention strategies, categorizing them into task-oriented intervention, sensory-motor intervention, and integrated intervention. All intervention methods demonstrated notable improvements in the legibility of handwriting. Comparison between domestic and international literature revealed a predominant use of task-oriented intervention in domestic studies, while international studies showcased a diverse range of intervention methods. Conclusion : Interventions were categorized into computer-based, task-oriented, sensory-motor, and integrated interventions. Task-oriented interventions were the most common in both domestic and international studies, while integrated interventions were the most effective. Based on these findings, it is necessary to increase awareness of the need for handwriting intervention research among occupational therapists in Korea. Additionally, there is a need for well-supported handwriting intervention research with larger sample sizes in both domestic and international occupational therapy. Finally, future research should actively investigate the application of tailored integrated interventions for school-aged children with handwriting difficulties.

• The Journal of the Korea Contents Association
• /
• v.14 no.10
• /
• pp.416-428
• /
• 2014

This study aimed to identify middle school students' perceptions and practices of handwriting, and factors affecting their attitudes towards handwriting. Data were collected by means of a survey targeting 346 students enrolled in 9 middle schools(Male=172, Female=172, Unknown=2, M=13.5 years old, SD= .94). Interviews, too, were conducted with 12 students in order to identify the students' perceptions of handwriting. The analyses of both survey and interview data revealed the following: (1) the majority of the interviewee students believed that handwriting is useful for memory and summarization so as to get a better school grade, including performance evaluations; (2) Many of the interviewee students were unsatisfied with their handwriting skills, giving higher scores to their peers' handwriting; (3) 45.7% of the students reported that mother was the one who taught them how to write for the first time; and 49.7% of them had no learning experience of taking notes; (4) Girls than boys and 1st graders than 2 or 3 graders showed more positive attitude towards handwriting; and (5) A multiple regression analysis showed that all the variables entered in the regression model, including sex, grade, affective attitude toward hands-on activities, physical abilities, time spent using a computer, and perceptions of Korean characters, had significant impacts on the students' attitudes towards handwriting.

• Journal of KIISE:Software and Applications
• /
• v.36 no.12
• /
• pp.1009-1015
• /
• 2009

Handwriting verification is a technique of distinguishing the same person's handwriting specimen from imitations with any two or more texts using one's handwriting individuality. This paper suggests an effective verification method for the handwritten signature or text on the off-line environment using pattern recognition technology. The core processes of the method which has been researched in this paper are extraction of letter area, extraction of features employing structural characteristics of handwritten text, feature analysis employing DTW(Dynamic Time Warping) algorithm and PCA(Principal Component Analysis). The experimental results show a superior performance of the suggested method.

• Journal of the Korea Society for Simulation
• /
• v.14 no.3
• /
• pp.147-154
• /
• 2005

In conventional approaches such as a functinal approach or a parametric approach to online signature verification, which could not deal with the local shape of signature, much various important informations inherent in the local part of signature shape have been overlooked. In this paper, we try a structural approach in which a signature is represented as a structural form of handwriting primitives and the local parts along a signature handwriting can be selectively compared according to their discrimination power in the process of signature verification, As a result, the error rate is diminished in the case that the weights of subpattern units is applied into comparing process, which is the degree of discrimination power of local part. And also, the global variation and complexity of each signature extracted from the analysis of local shape is found useful in determining the decision threshold more precisely.

• The Journal of Korean Academy of Sensory Integration
• /
• v.17 no.1
• /
• pp.1-8
• /
• 2019

Objective : This paper aimed to measure the relationship between the performance of Korean handwriting and visual fixation for children. Methods : Twenty-one typically developing children aged 7 to 9 years participated in the study. The children performed Korean handwriting task wearing Tobii Pro Glasses 2. The Korean handwriting task consisted of 10 words from elementary school textbooks. The handwriting skill was measured by the coefficient variation of the letter size and the fixation cound and duration. Correlation analysis was performed to investigate the relation between visual fixation and the coefficient variation of the letter size. Results : The results showed that the visual fixation per second was positively correlated with Korean handwriting vertical size coefficient variation, indicating that the more consistent the vertical size of the letter, the smaller the fixation count per second. Conclusion : The results suggested a relation between the performance of Korean handwriting and visual fixation in typically developing children. This study is the first attempt to measure eye movement during the Korean handwriting process, and suggests a future direction for research on students' development in writing Korean.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.1
• /
• pp.63-68
• /
• 2010

Recently, to accelerate the Ubiquitous generation, the input interface of the mobile machinery and tools are actively being researched. In addition with the existing interfaces such as the keyboard and curser (mouse), other subdivisions including the handwriting, voice, vision, and touch are under research for new interfaces. Especially in the case of small-sized mobile machinery and tools, there is a increasing need for an efficient input interface despite the small screens. This is because, additional installment of other devices are strictly limited due to its size. Previous studies on handwriting recognition have generally been based on either two-dimensional images or algorithms which identify handwritten data inserted through vectors. Futhermore, previous studies have only focused on how to enhance the accuracy of the handwriting recognition algorithms. However, a problem arisen is that when an actual handwriting is inserted, the user must select the classification of their characters (e.g Upper or lower case English, Hangul - Korean alphabet, numbers). To solve the given problem, the current study presents a system which distinguishes different languages by analyzing the form/shape of inserted handwritten characters. The proposed technique has treated the handwritten data as sets of vector units. By analyzing the correlation and directivity of each vector units, a more efficient language distinguishing system has been made possible.

• Korean Journal of Occupational Therapy
• /
• v.26 no.4
• /
• pp.43-55
• /
• 2018

Objective : The purpose of this study was to investigate the effects of fidget spinner training on the hand function and handwriting legibility of lower grade elementary school studens. Methods : This study randomly assigned a study group of 12 children and control group of 12 children from 24 children in grade 1 and 2 (ages 7 through 8), whose are dominantly right handed. The study used was a pre-post process. The intervention was conducted only on the study group twice a week for 5 weeks and for 40 minutes per session, for a total of ten sessions. The measuring instruments used to compare the hand functions and handwriting legibility were the Jebsen-Taylor Hand Function Test, Grip Strength Test, and Legibility Test. The data analysis used a Wilcoxon signed rank, Mann-Whitney U and Chi-Square cross analysis. Results : The fidget spinner training showed significant improvement in the study group's hand function(grip strength and handwriting legibility) and a significant difference was shown between the control and study groups. Conclusion : This study confirmed the value and utility of a fidget spinner as a tool for improving the hand function and handwriting legibility of elementary school students in lower grades. Future studies are expected to verify the effectiveness of the fidget spinner training based on the present study.

• ETRI Journal
• /
• v.46 no.4
• /
• pp.648-659
• /
• 2024

Author verification is challenging because of the diversity in writing styles. We propose an enhanced handwriting verification method that combines handcrafted and automatically extracted features. The method uses a genetic algorithm to reduce the dimensionality of the feature set. We consider offline Bangla handwriting content and evaluate the proposed method using handcrafted features with a simple logistic regression, radial basis function network, and sequential minimal optimization as well as automatically extracted features using a convolutional neural network. The handcrafted features outperform the automatically extracted ones, achieving an average verification accuracy of 94.54% for 100 writers. The handcrafted features include Radon transform, histogram of oriented gradients, local phase quantization, and local binary patterns from interwriter and intrawriter content. The genetic algorithm reduces the feature dimensionality and selects salient features using a support vector machine. The top five experimental results are obtained from the optimal feature set selected using a consensus strategy. Comparisons with other methods and features confirm the satisfactory results.