• ETRI Journal
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• v.37 no.1
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• pp.138-146
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• 2015

This paper presents a new non-constraining online optical handwritten signature reconstruction system that, in the main, makes use of a transparent glass pad placed in front of a color camera. The reconstruction approach allows efficient exploitation of hand activity during a signing process; thus, the system as a whole can be seen as a viable alternative to other similar acquisition tools. This proposed system allows people with physical or emotional problems to carry out their own signatures without having to use a pen or sophisticated acquisition system. Moreover, the developed reconstruction signature algorithms have low computational complexity and are therefore well suited for a hardware implementation on a dedicated smart system.

• ETRI Journal
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• v.40 no.6
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• pp.774-787
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• 2018

Arabic handwriting segmentation and recognition is an area of research that has not yet been fully understood. Dealing with Arabic ligature segmentation, where the Arabic characters are connected and unconstrained naturally, is one of the fundamental problems when dealing with the Arabic script. Arabic character-recognition techniques consider ligatures as new classes in addition to the classes of the Arabic characters. This paper introduces an enhanced technique for Arabic handwriting recognition using the deep belief network (DBN) and a new morphological algorithm for ligature segmentation. There are two main stages for the implementation of this technique. The first stage involves an enhanced technique of the Sari segmentation algorithm, where a new ligature segmentation algorithm is developed. The second stage involves the Arabic character recognition using DBNs and support vector machines (SVMs). The two stages are tested on the IFN/ENIT and HACDB databases, and the results obtained proved the effectiveness of the proposed algorithm compared with other existing systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1201-1206
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• 2014

Retail stores are mostly relying their product management on handwriting. This handwriting management is limited and poor at managing the status of stocking and releasing. Also, to confirm real-time product status, additional statistic system is required. POS system developed to overcome foresaid problems is operating only in big and special stores because of expensive price and limited space. Therefore, new automated management system which has low installation price needs to be developed and adopted instead of handwriting management system. In this paper, we developed real-time product management system which can manage the products in retail stores by utilizing NFC function in mobile device.

• International Journal of Contents
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• v.11 no.3
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• pp.7-13
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• 2015

One of the biggest problems of skeletonization is the occurrence of distortions at the junction point of the final binary image. At the junction area, a single point usually becomes a small stroke, and the corresponding trajectory task, as well as the OCR, consequently becomes more complicated. We therefore propose an adaptive post-processing method that uses an adaptive threshold technique to correct the distortions. Our proposed method transforms the distorted segments into a single point so that they are as similar to the original image as possible, and this improves the static handwriting images after the skeletonization process. Further, we attained promising results regarding the usage of the enhanced skeletonized images in other applications, thereby proving the expediency and efficiency of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.892-898
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• 2012

Rough classification methods are used to improving the recognition speed in many character recognition problems. In this case, some irreversible result can occur by an error in rough classification. Methods for duplicating each model in several classes are used in order to reduce this risk. But the errors by rough classfication can not be completely ruled out by these methods. In this paper, an recognition method is proposed to increase speed that matches models selectively without any increase in error. This method constructs a model graph using similarity between models. Then a search process begins from a particular point in the model graph. In this process, matching of unnecessary models are reduced that are not similar to the input pattern. In this paper, the proposed method is applied to the recognition problem of handwriting numbers and upper/lower cases of English alphabets. In the experiments, the proposed method was compared with the basic method that matches all models with input pattern. As a result, the same recognition rate, which has shown as the basic method, was obtained by controlling the out-degree of the model graph and the number of maintaining candidates during the search process thereby being increased the recognition speed to 2.45 times.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.211-216
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• 2001

Recently, the research for the mobile computing such as PDA, Palm PC and wearable computing related technologies is widely under development, specially for the input device. Among the mobile input methods are speech recognition, handwriting recognition and cording type. However these systems have the problems of the data input appraratus like input speed and recognition rate. This paper presents the Glove-based input device which could solve the system's data input problem. By the experimental results suggest the method of proposional input method that utilize the hand's movement is appropriate for the effective mobile input devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3594-3607
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• 2017

The traditional feature extraction methods such as principal component analysis (PCA) cannot obtain the local structure of the samples, and locally linear embedding (LLE) cannot obtain the global structure of the samples. However, a common drawback of existing PCA and LLE algorithm is that they cannot deal well with the sparse problem of the samples. Therefore, by integrating the globality of PCA and the locality of LLE with a sparse constraint, we developed an improved and unsupervised difference algorithm called Sparse Difference Embedding (SDE), for dimensionality reduction of high-dimensional data in small sample size problems. Significantly differing from the existing PCA and LLE algorithms, SDE seeks to find a set of perfect projections that can not only impact the locality of intraclass and maximize the globality of interclass, but can also simultaneously use the Lasso regression to obtain a sparse transformation matrix. This characteristic makes SDE more intuitive and more powerful than PCA and LLE. At last, the proposed algorithm was estimated through experiments using the Yale and AR face image databases and the USPS handwriting digital databases. The experimental results show that SDE outperforms PCA LLE and UDP attributed to its sparse discriminating characteristics, which also indicates that the SDE is an effective method for face recognition.

• The Korean Journal of Elementary Counseling
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• v.7 no.1
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• pp.135-163
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• 2008

This study intends to confirm if it is effective in improving the problem behaviors by applying "Logical Consequence" suggested by Adler to the class management. The researcher who is in charge of the 4th grade class of elementary school in G city applied Adlerian logical consequence to her children, observed and examined the effectiveness of reducing the problem behaviors by the qualitative study method of in-depth interview from March to October. The problem behaviors treated in this study includes irrelevant remarks and gossip in school time, no preparation for taking lessons in time, no preparation of a textbook and a supply, no involvement in doing homework, scribbling and poor handwriting on a textbook, teasing a friend (abusive language, joking, violence), indoor running, no involvement in doing a task, being late and no arrangement of indoor shoes. In conclusion, this study indicated that the use of Logical Consequence was relatively effective in improving the problem behaviors and more effective in individual behaviors rather than group's behaviors. While the problem behaviors conducted in a class in the daily routine were effective at the point of the occurred problems, the problem behaviors occurred at the point of time related to a home or the finish of daily routine were ineffective.

• KIISE Transactions on Computing Practices
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• v.24 no.1
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• pp.33-39
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• 2018

For the integration test in the current field of defense simulation, each actual equipment and simulator's logging information is automated. Although the event of the integrated test system is written in the test log, it is not automated, and relies on the operator's handwriting or file creation, resulting in ineffective aspects such as low-quality record content and repetition of the same content. In this study, we propose the automatic test report recording program that solves these problems. Automatic test report recording program uses framework-based technology to receive information from the test control computer and user to record a log of the test log. Automatic test report recording program allows the user to record the repeated test content in a stable manner. Additionally, even if the number of test operators is limited, the efficiency is improved so that we can fucus on the integration test.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.790-791
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• 2016

The system used in the laboratory of chemistry and medical is management only by measuring the temperature inside the reagent management within and recording in handwriting. When you hold the reagent, it can not recognize in real time the problems that occur in the interior, an accident occurs. you can not find a use record reagent storage, a problem with the management of an efficient reagent can be generated. In this paper, we propose a reagent management system that leverages the embedded boards and sensors in the laboratory reagents effectively manage to resolve it. As a result, Converting the information of the reagent to the data using the NFC, the administrator can identify the reagent user to register and manage hazardous reagents. Converted by using the NFC information of the reagent to the data, the administrator can identify the reagent user to register and manage hazardous reagents, temperature, humidity, so that it can be controlled by utilizing the VOC sensor to. Also it is passes the message to the administrator in the event of a particular risk situation. This is believed to enable the effective administration in a laboratory reagent.