• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.724-733
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• 2017

Conventional methods of automatically recording Go game positions do not properly consider obstacles (hand or object) on a Go board during the Go game. If the Go board is blocked by obstacles, the position of a Go stone may not be correctly recognized, or the sequences of moves may be stored differently from the actual one. In the proposed algorithm, only the complete Go board image without obstacles is stored as a background image and the obstacle is recognized by comparing the background image with the current input image. To eliminate the phenomenon that the shadow is mistaken as obstacles, this paper proposes the new obstacle detection method based on the gradient image instead of the simple differential image. When there is no obstacle on the Go board, the background image is updated. Finally, the successive background images are compared to recognize the position and type of the Go stone. Experimental results show that the proposed algorithm has more than 95% recognition rate in general illumination environment.

• Journal of radiological science and technology
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• v.40 no.2
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• pp.237-243
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• 2017

This study evaluated the applicability of computer-aided diagnosis by retrospective analysis of GLCM algorithm based on cytopathological diagnosis of normal and malignant nodules in thyroid ultrasound images. In the experiment, the recognition rate and ROC curve of thyroid malignant nodule were analyzed using 6 parameters of GLCM algorithm. Experimental results showed 97% energy, 93% contrast, 92% correlation, 92% homogeneity, 100% entropy and 100% variance. Statistical analysis showed that the area under the curve of each parameter was more than 0.947 (p = 0.001) in the ROC curve, which was significant in the recognition of thyroid malignant nodules. In the GLCM, the cut-off value of each parameter can be used to predict the disease through analysis of quantitative computer-aided diagnosis.

• Journal of Korea Multimedia Society
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• v.4 no.3
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• pp.238-246
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• 2001

We have developed the sign-language synthesis system, which can be applied for intelligent terminal equipments, for the purpose of communications between normal people and the hearing-impaired. In the system, we generate the behavior of the sign-language words using CG animation based on Motion-Primitives of the motion observed of each legion of the body in the generation of words, the conventional system was difficult to control the shape of hands and the motions of hands and shoulder, requiring lots of time for the processing. Also it is a big problem to make a large database of sign-language, because it requires over 5,000 words to translate the sign-language. Therefore, in this paper, we propose the new system that is easy to construct the database by using Motion-Primitives, which can make paths of various motions more smooth than conventional systems. We have tested 100 words of the sign-language against the hearing-impaired with the proposed system. As the result of testing by the proposed system, we have earned a good recognition rate with 82%. On the other hand, we had earned the recognition ratio with 76% by using the former system.

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.17-33
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• 2005

This paper presents the proposed a classifier of liver cirrhotic step using MR(magnetic resonance) imaging and hierarchical neural network. The data sets for classification of each stage, which were normal, 1type, 2type and 3type, were analysis in the number of data was 231. We extracted liver region and nodule region from T1-weight MR liver image. Then objective interpretation classifier of liver cirrhotic steps. Liver cirrhosis classifier implemented using hierarchical neural network which gray-level analysis and texture feature descriptors to distinguish normal liver and 3 types of liver cirrhosis. Then proposed Neural network classifier learned through error back-propagation algorithm. A classifying result shows that recognition rate of normal is $100\%$, 1type is $82.8\%$, 2type is $87.1\%$, 3type is $84.2\%$. The recognition ratio very high, when compared between the result of obtained quantified data to that of doctors decision data and neural network classifier value. If enough data is offered and other parameter is considered this paper according to we expected that neural network as well as human experts and could be useful as clinical decision support tool for liver cirrhosis patients.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.142-152
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• 2016

GPS is not able to be used for indoor positioning and currently most of techniques emerging to overcome the limit of GPS utilize private wireless networks. However, these methods require high costs for installation and maintenance, and they are inappropriate to be used in the place where precise positioning is needed as in indoor parking lots. This paper proposes a vehicular indoor positioning method based on QR-code recognition. The method gets an absolute coordinate through QR-code scanning, and obtain the location (an relative coordinate) of a black-box camera using the tilt and roll angle correction through affine transformation, scale transformation, and trigonometric function. Using these information of an absolute coordinate and an relative one, the precise position of a car is estimated. As a result, average error of 13.79cm is achieved and it corresponds to just 27.6% error rate in contrast to 50cm error of the recent technique based on wireless networks.

• The Journal of Korean Medicine
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• v.27 no.2 s.66
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• pp.111-121
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• 2006

Objectives : The purpose of this study was to identify attitude, treatment and quality control of Oriental medicines and to find the influencing factors affecting them. Methods : We made a survey of 213 people who work in the field of Oriental medicine in Daegu. A survey on attitudes about treatment, and quality control of Oriental medicines was conducted by mail. The data was analyzed by SPSS. Results : The survey results showed that most common purchase place for Oriental medicine was a wholesale market (67.0%). Storage of Oriental medicine was mostly in warehouse (61.4%) without temperature controls. Subjects expressed necessity for quality control (100%), legal controls (96.2%), grading according to quality (95.7%), and standardization of Oriental medicine (90.6%) at a high rate. Conclusions : These results showed that subjects were interested in quality control of Oriental medicine to ensure safety.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.621-625
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• 2010

This paper presents a hand motion tracking method for hand gesture interface using a camera in mobile devices such as a smart phone and PDA. When a camera moves according to the hand gesture of the user, global optical flows are generated. Therefore, robust hand movement estimation is possible by considering dominant optical flow based on histogram analysis of the motion direction. A continuous hand gesture is segmented into unit gestures by motion state estimation using motion phase, which is determined by velocity and acceleration of the estimated hand motion. Feature vectors are extracted during movement states and hand gestures are recognized at the end state of each gesture. Support vector machine (SVM), k-nearest neighborhood classifier, and normal Bayes classifier are used for classification. SVM shows 82% recognition rate for 14 hand gestures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.722-727
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• 2009

The technology of distinguishing human motion states is required in the areas of measuring and analyzing biosignals changing according to physical activities, diagnosing sleep disorder, screening the effect of treatment, examining chronic patients' kinetic state, prescribing exercise therapy, etc. The present study implemented a fuzzy inference system based on fuzzy rules that distinguish human motion states (tying, sitting, walking, and running) by acquiring and processing data of LAA, TAA, L-MAD, and T-MAD using ADXL202AE of Analog Devices embedded in an armband. The membership degree and fuzzy rules in each area of input (LAA, TAA, L-MAD, and T-MAD) and output (tying, sitting, walking, and running) data used here were determined using numeric data obtained from experiment. In the results of analyzing data for simulation generated in order of tying$\rightarrow$walking$\rightarrow$running$\rightarrow$tying, the sorting rate for motion states tying, sitting, walking, and running was 100% for each motion.

• Journal of KIISE:Software and Applications
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• v.34 no.9
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• pp.857-868
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• 2007

The good classifier ensemble should have a high complementarity among classifiers in order to produce a high recognition rate and its size is small in order to be efficient. This paper proposes a classifier ensemble selection algorithm with coarse-to-fine stages. for the algorithm to be successful, the original classifier pool should be sufficiently diverse. This paper produces a large classifier pool by combining several different classification algorithms and lots of feature subsets. The aim of the coarse selection is to reduce the size of classifier pool with little sacrifice of recognition performance. The fine selection finds near-optimal ensemble using genetic algorithms. A hybrid genetic algorithm with improved searching capability is also proposed. The experimentation uses the worldwide handwritten numeral databases. The results showed that the proposed algorithm is superior to the conventional ones.

• The Journal of the Korea Contents Association
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• v.14 no.12
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• pp.665-673
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• 2014

The Korean film market has revved up against American movies and the movie industry has continued to grow even though Korea is a small country. However, most production staffs who are responsible for practical business of film production get wages that fall short of the inflation rate and minimum wages as temporary employees. And there's the atmosphere that they try to leave film sites on the first opportunity. This study finds that the cause to leave film sites is attributed to perception gaps about the hardworking character and labor which occur in the process that production staffs enter the movie industry and participate in film production as well as poor surroundings. And it should establish staffs' hardworking character and recognition as workers to them by reorganizing the current curriculums which approach movies from the only artistic viewpoint in the departments related to movies and images that hold a large majority in their majors, establishing the concept of work according to participation in film production to potential production staffs, and changing their recognition to improve the elements that they leave the sites.