• Journal of The Korean Society of Integrative Medicine
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• v.3 no.1
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• pp.1-10
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• 2015

Purpose: This study investigated the relationships of handwriting legibility and perceptual-motor skills, and handwriting speed and perceptual-motor skills. And identified the predictors that most affect the handwriting of preschool children. Methods: Twenty-three typically developing preschool aged children (mean age: 68.61 months, SD=2.04) were selected through the Korean-Denver Developmental Screening Test-2(K-DDST-2). The children were tested with regard to handwriting legibility, visual perception, visual-motor integration and fine-motor coordination. Results: First, a significant relationship was not found among handwriting legibility, visual perception, visual-motor integration and fine-motor coordination. Second, a significant relationship was found among handwriting speed, visual perception and fine-motor coordination. Third, stepwise multiple regression analyses showed that general visual perception were significant predictors for handwriting speed. Conclusion: Occupational therapists should evaluate children's visual perception levels utilizing a standardized test, and focus on general visual perception in order to improve handwriting skill(speed). Also, occupational therapists are expected to play an important role in the management and treatment of children's handwriting skills.

• The Journal of Korean Academy of Sensory Integration
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• v.9 no.1
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• pp.21-31
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• 2011

Objective : This study investigated the relationships of handwriting legibility and perceptual-motor skills, and handwriting speed and perceptual-motor skills. And identified the predictors that most affect the handwriting of preschool children. Methods : Twenty-three typically developing preschool aged children (mean age: 68.61 months, SD=2.04) were selected through the Korean-Denver Developmental Screening Test-2(K-DDST-2). The children were tested with regard to handwriting legibility, visual perception, visual-motor integration and fine-motor coordination. Results : First, a significant relationship was not found among handwriting legibility, visual perception, visualmotor integration and fine-motor coordination. Second, a significant relationship was found among handwriting speed, visual perception and fine-motor coordination. Third, stepwise multiple regression analyses showed that general visual perception were significant predictors for handwriting speed. Conclusion : Occupational therapists should evaluate children's visual perception levels utilizing a standardized test, and focus on general visual perception in order to improve handwriting skill(speed). Also, occupational therapists are expected to play an important role in the management and treatment of children's handwriting skills.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1435-1441
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• 2018

Online signature verification is one of the simple and efficient methods of identity verification and has less resistance than other biometric technologies. To handle signature verification as a classification problem, it is necessary to gather forgery signatures, which is not easy in most practical applications. It is not easy to obtain a large number of genuine signatures either. In this paper, one class SVM is used to tackle the forgery signature problem and someone else's signatures are used as general handwriting data to solve the genuine signature problem. Someone else's signature does not share shape-based features with the signature to be verified, but it contains the general characteristics of a signature and useful in verification. Verification rate can be improved by using the general handwriting data, which can be confirmed through the experimental results.

• Journal of KIISE:Software and Applications
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• v.35 no.4
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• pp.245-254
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• 2008

This paper proposes a unified multi-modal input framework to interface the recognition engines such as IBM ViaVoice and Microsoft handwriting-recognition system with general window applications, particularly, for pen-input displays. As soon as user pushes a hardware button attached to the pin-input display with one hand, the current window of focus such as a internet search window and a word processor is overlaid with a transparent window covering the whole desktop; upon which user inputs handwriting with the other hand, without losing the focus of attention on working context. As well as freeform handwriting on this transparent input overlay as a sketch pad, the user can dictate some words and draw diagrams to communicate with the system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2298-2304
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• 2017

Online signature verification is one of the simple and efficient method of identity verification and has less resistance than other biometric technologies. In training to build a verification model, negative samples are required to build the model, but in most practical applications it is not easy to get negative samples - forgery signatures. In this paper, proposed is a method using someone else's signatures as negative samples. In verification, shape-based features extracted from the time-sequenced signature data are extracted and a support vector machine is used to verify. SVM tries to map a feature vector to a high dimensional space and to draw a linear boundary in the high dimensional space. SVM is one of the best classifiers and has been applied to various applications. Using general handwriting data, i.e., someone else's signatures which have little in common with positive samples improved the verification rate experimentally, which means that signature verification without negative samples is possible.

• Communications for Statistical Applications and Methods
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• v.28 no.6
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• pp.583-594
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• 2021

In this paper, we propose wavelet-based procedures to identify the difference between images, including portraits and handwriting. The proposed methods are based on a novel combination of multiscale methods with a regularization technique. The multiscale method extracts the local characteristics of an image, and the distinct features are obtained through the regularized regression of the local characteristics. The regularized regression approach copes with the high-dimensional problem to build the relation between the local characteristics. Lytle and Yang (2006) introduced the detection method of forged handwriting via wavelets and summary statistics. We expand the scope of their method to the general image and significantly improve the results. We demonstrate the promising empirical evidence of the proposed method through various experiments.

• Korean Journal of Heritage: History & Science
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• v.46 no.2
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• pp.150-165
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• 2013

This study aims to investigate the original position, the writer of signboard handwriting and the period of Wibongmun and Joyangru in order to restore Wibongmun and Joyangru which have been designated as tangible cultural properties (有形文化財). They also have to be moved in the Gangwon Provincial Office. Wibongmun and Joyangru were established as government offices in chuncheon(春川官衙) and they were used as attached buildings in Chunceon (春川離宮) in 1890. Wibongmun was moved to Gangwon Provincial Office 5 times and Joyangru was moved twice. In order to move them back to the original place, by using the topographic map made by the Japanese Government-General in Korea, we find out Joyangru was located in the exit of Gangwon Provincial Office and greenhouse and we also figure out Wibongmun was located in the garden. While we study historical evidence on handwriting, we also find out the handwriting of Joyangmun was written by Songhaong (松下翁) Jo, Yun-Hyeong (曺允亨). Especially, Joyangru had played a role as a government office and it may be called 'Joyangru' after reconstructing 'Joyangmun' when attached buildings were established. Through this study, we found that the first period and reason of establishing Wibongmun and Joyangru was at least before 1788. Through this study, we can find the period of both and its historic meaning more clearly.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.540-543
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• 2020

본 논문에서는 대표적인 이미지 분류 모델인 CNN(Convolutional Neural Network)과 시간에 따른 이미지의 변화를 학습할 수 있는 LSTM(Long Short-Term Memory) 기반의 온라인 서명인식 모델을 제안한다. 실제로는 위조서명을 미리 구하기 어렵다는 사실을 고려해 서명검증 대상자가 아닌 타인의 진서명과 대상자의 일반 필기 데이터를 음의 데이터로서 학습에 사용하였다. 실험 결과, 전체 이미지 중 서명 부분의 비율에 따라 좋은 성능을 보이는 검증 모델이 다르며 Accuracy 성능지표를 통해 이 비율이 높거나 낮을 경우 CNN-LSTM 이, 중간일 경우 CNN 이 적합하다는 것을 확인하였다.

• The Journal of the Convergence on Culture Technology
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• v.3 no.4
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• pp.165-169
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• 2017

CNN(Convolutional Nerual Network) is one of the algorithms that show superior performance in image recognition and classification among machine learning algorithms. CNN is simple, but it has a large amount of computation and it takes a lot of time. Consequently, in this paper we performed an parallel processing unit for the convolution layer, pooling layer and the fully connected layer, which consumes a lot of handling time in the process of CNN, through the SIMT(Single Instruction Multiple Thread)'s structure of GPGPU(General-Purpose computing on Graphics Processing Units).And we also expect to improve performance by reducing the number of memory accesses and directly using the output of convolution layer not storing it in pooling layer. In this paper, we use MNIST dataset to verify this experiment and confirm that the proposed CNN structure is 12.38% better than existing structure.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.37-44
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• 2006

In this paper, a new version of the ICM method(MICM, modified ICM) in which the contextual information is modelled by Markov random fields (MRF) is introduced. To extract the feature, a new local MRF model with a fitting block neighbourhood is proposed. This model selects contextual information not only from the relative intensity levels but also from the geometrically directional position of neighbouring cliques. Feature extraction depends on each block's contribution to the local variance. They discriminates it into several regions, for example context and background. Boundaries between these regions are also distinctive. The proposed algerian performs segmentation using directional block fitting procedure which confines merging to spatially adjacent elements and generates a partition such that pixels in unified cluster have a homogeneous intensity level. From experiment with ink rubbed copy images(Takbon, 拓本), this method is determined to be quite effective for feature identification. In particular, the new algorithm preserves the details of the images well without over- and under-smoothing problem occurring in general iterated conditional modes (ICM). And also, it may be noted that this method is applicable to the handwriting recognition.