• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.71-82
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• 1995

The readability and the visuability are very significant when the letters or figures are displayed as static visual information. Not only is the beauty of the body type character(small letters) important but the display type character(large letters) should also be read easily, quickly and precisely. The issue regarding the readability in terms of perception of information has been raised continuously for all kinds of small signage and billboard, etc., which are written in display type within our everyday life. Among the various kinds of small signage and billboards the car licence plate is well known. Among all the possible factors that would have made an impact on the readability of licence plate, this paper focused on the effects of arrangement of character(letters and figures) and contrast of colors for the readability of licence plate using the within-subject analysis. The statistical analysis results in error reading rate, the character arrangement were significant but the color contrast(green/white, white/green, blue/white, white/blue, black/yellow) was not, No interaction was found.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.101-105
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• 2016

After a weight-rate disposal system for food waste has been implemented we have to install the food waste system at all apartment. In this paper, we supplied electric energy to the food waste system using solar heat panels. The weight of the food waste is displayed on the LCD panel, and its price is calculated based on its weight. Since there would be some cases that touch-typed card can't be well recognized if it is contaminated by foreign material, we designed a recognition device by no-touch sensitive card reader to embody the food waste system. The food waste system was designed using a GUI(graphical user interface) so that users can easily understand it.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1472-1475
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• 1999

This paper proposes a new detection method of human faces in grey scale images with cluttered background using a facial template and elliptical structure of the human head. Face detection technique can be applied in many areas of image processing such as face recognition, composition and computer graphics, etc. Until now, many researches about face detection have been done, and applications in more complicated conditions are increasing. The existing technique proposed by Sirohey shows relatively good performance in image with cluttered background, but can apply only to image with one face and needs much computation time. The proposed method is designed to reduce complexity and be applied even in the image with several faces by introducing template matching as preprocess. The results show that the proposed method produces more correct detection rate and needs less computation time than the existing one.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.5
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• pp.277-282
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• 2003

In this paper we propose Using Higher Order Neuron on the Supervised Learning Machine of the Kohonen Feature Map. The architecture of proposed model adopts the higher order neuron in the input layer of Kohonen Feature Map as a Supervised Learning Machine. It is able to estimate boundary on input pattern space because or the higher order neuron. However, it suffers from a problem that the number of neuron weight increases because of the higher order neuron in the input layer. In this time, we solved this problem by placing the second order neuron among the higher order neuron. The feature of the higher order neuron can be mapped similar inputs on the Kohonen Feature Map. It also is the network with topological mapping. We have simulated the proposed model in respect of the recognition rate by XOR problem, discrimination of 20 alphabet patterns, Mirror Symmetry problem, and numerical letters Pattern Problem.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.2
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• pp.236-243
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• 2016

This paper presents a threat list acquisition method in an engagement area using the support vector machines (SVM). The proposed method consists of track creation, track estimation, track feature extraction, and threat list classification. To classify the threat track robustly, dynamic track estimation and pattern recognition algorithms are used. Dynamic tracks are estimated accurately by approximating a track movement using position, velocity and time. After track estimation, track features are extracted from the track information, and used to classify threat list. Experimental results showed that the threat list acquisition method in the engagement area achieved about 95 % accuracy rate for whole test tracks when using the SVM classifier. In case of improving the real-time process through further studies, it can be expected to apply the fire control systems.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2707-2715
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• 1999

Recently, there have been researches to automate processing and analysing images in the medical field using image processing technique, a fast communication network, and high performance hardware. In this paper, we propose a system to be able to analyze morphological abnormality of red-blood cells for peripheral blood image using image processing techniques. To do this, we segment red-blood cells in the blood image acquired from microscope with CCD camera and then extract UNL fourier features to classify them into 15 classes. We reduce the number of multi-variate features using PCA to construct a more efficient classifier. Our system has the best performance in recognition rate, compared with two other algorithms, LVQ3 and k-NN. So, we show that it can be applied to a pathological guided system.

• Annual Conference of KIPS
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• 2003.05a
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• pp.583-586
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• 2003

보안이 점점 큰 의미를 가지는 요즘, 생체정보를 개인 신분 확인수단으로 이용하려는 연구가 많이 이루어지고 있다 생체정보를 이용한 분야로는 얼굴 인식, 지문 인식, 정맥 인식, 홍채 인식 등이 있는데 그 중에서도 홍채는 패턴의 불변성과 개인의 정보로 이용될 수 있을 정도로 다양한 패턴 형태를 이루고 있다. 이러한 홍채를 이용하여 신분을 인식하기 위해서는 불필요한 영역은 배제하고 인식을 위한 특징만을 가지고 있는 영역을 정확히 찾는 것이 중요하다고 하겠다. 또한 인식 시간의 단축을 위해서 특징 데이터의 크기를 줄이기 위한 방법도 고려되어야 한다. 이 두 가지 문제를 해결하기 위하여 본 논문에서는 홍채의 특징이 가장 많이 분포되어 있는 영역을 찾기 위한 전처리 기법과 인식을 위한 신경망에서 인식시간을 단축하면서 인식률을 높일 수 있는 최적의 신경망 구조를 찾아내는 방법을 제안한다.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.05b
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• pp.100-103
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• 2004

In this paper, BP learning algorithm is studied to apply as a PD source classification in GIS specimens. For occurred partial discharge, three defected models are made; floating particle, surface discharge of spacer, needle to plane. And PD data for discrimination were acquired from PD detector. And these data making use of a computer-aided discharge analyser, statistical and other discharge parameters is calculated to discrimination between different models of discharge sources. And also these parameter is applied to classify PD sources by neural networks. Neural Networks has good recognition rate for three PD sources.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.3
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• pp.83-89
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• 2008

This paper introduces a visual object classification algorithm based on statistical information. Objects are characterized through the Histogram of Oriented Gradients (HOG) method and classification is performed using Multiclass AdaBoost. Salient features of an object's appearance are detected by HOG blocks Blocks of different sizes are tested to define the most suitable configuration. To select the most informative blocks for classification a multiclass AdaBoostSVM algorithm is applied. The proposed method has a high speed processing and classification rate. Results of the evaluation based on example of hand gesture recognition are presented.

• Korean Institute of Interior Design Journal
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• no.5
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• pp.30-36
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• 1995

Light plays an important role in making a continuity of space and in determining the distinctive expression and char-acter of a space. Particularly, the introduction of natural light derives from our esthetic needs, as well as from the fundamental biologi-cal necessities of human beings. And also, adaptation to time and space is the vital factor of human survival and prosperity. Our visual recognition of light is usually formed not only by practical illumination but by analogy, expection and expe-rienced of lighting itself. As the forecase of natural light is (almost) impossible be-cause of variables such as changing weather, reflection rate of light and the patterns of shade, in designing the introduc-tion of daylight, there should be follow-ed careful considera-tion of the adaptation to such variety and the impet-us of light. The research was conducted to mane a contribution to cre-ate more rich and beautiful interior spaces by studying the characteristic of light which is one of the important factors of interior space design, and by inquiring the way to intro-duce light and its effect through the practical examples of Alvar Aalto, Le Corbusier and Louis I. Kahn.