• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.859-866
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• 2023

This paper focuses on configuring a user-friendly system of LED systems by applying improvement measures such as gamma correction, non-flicker, and driving noise removal using MCUs and LED drivers. As a result of the experiment, the 22kHz PWM mode of the LED driver generated noise outside the audible frequency range, making it practically imperceptible to users. The appropriate pull-up resistor values within the normal operating delay ratio of 5% were found to be 1kΩ to 10kΩ for the 3kHz PWM mode and 1kΩ to 2kΩ for the 22kHz PWM mode. In addition, gamma correction can be optimized for nonlinear human visual systems to express accurate contrast and as a result, it is expected to develop an LED system that can be expressed more naturally and accurately than conventional LED systems and improve users' visual experience.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.90-101
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• 2012

The landmark selection is crucial to successful perform in SLAM(Simultaneous Localization and Mapping) with a mono camera. Especially, in unknown environment, automatic landmark selection is needed since there is no advance information about landmark. In this paper, proposed visual attention system which modeled human's vision system will be used in order to select landmark automatically. The edge feature is one of the most important element for attention in previous visual attention system. However, when the edge feature is used in complicated indoor area, the response of complicated area disappears, and between flat surfaces are getting higher. Also, computation cost increases occurs due to the growth of the dimensionality since it uses the responses for 4 directions. This paper suggests to use a corner feature in order to solve or prevent the problems mentioned above. Using a corner feature can also increase the accuracy of data association by concentrating on area which is more complicated and informative in indoor environments. Finally, this paper will prove that visual attention system based on corner feature can be more effective in SLAM compared to previous method by experiment.

• Korean Business Review
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• v.23 no.2
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• pp.1-29
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• 2010

Traditional human resource management explains human characteristics with motivation, attitude, perception, value, etc., based upon behavioral science approach. And system approach is adopted in analyzing the interaction between people and the environment. However, personnel economics excludes social and psychological variables in the human choice models, and assumes very unrealistic and simple rational decision making process. For environmental variables, personnel economists considers only income and price. Traditional human resource management research model successfully explains the phenomenon for each specific situation, but lacks universality. On the other hand, personnel economics model is strict and analytical, but tends to distort the understanding of the results because of the unrealistic assumptions. These two academic fields may get benefits by introducing the other's research methodologies, theories, and ideas.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.565-570
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• 2013

The mirror neuron regions which are distributed in cortical area handled a functionality of intention recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper an automated intention recognition system is proposed by applying computational model of mirror neuron system to the human-robot interaction system. The computational model of mirror neuron system is designed by using dynamic neural networks which have model input which includes sequential feature vector set from the behaviors from the target object and actor and produce results as a form of motor data which can be used to perform the corresponding intentional action through the imitative learning and estimation procedures of the proposed computational model. The intention recognition framework is designed by a system which has a model input from KINECT sensor and has a model output by calculating the corresponding motor data within a virtual robot simulation environment on the basis of intention-related scenario with the limited experimental space and specified target object.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.10
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• pp.134-142
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• 2009

In this paper, we proposed the right-angle stereo vision system to measure the object size using a human eyesight-like, and the system is reconstructed with conventional stereo vision system. In this proposed system, the size results of objects are measured very close to the real object size, and we got the ratios 93~103[%] for the real object sizes. Therefore, the suggested right-angle stereo vision system have a high possibilities to be applied to many industrial system parts and to be used for robot system, automatic system, and etc.

• Science of Emotion and Sensibility
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• v.7 no.3
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• pp.15-25
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• 2004

The regression analysis and Adaptive -Network based Fuzzy-inference system (ANFIS) were applied to the explanation on human's visual texture of cotton fabrics with 7 mechanical properties. The ANFIS uses the structure with fuzzy membership function and neural network. The results obtained by the statistical analysis through the coefficient of correlation and regression analysis showed that subjective texture had a linear relationship with mechanical properties. But It had a relatively low coefficient of determination and was difficult that the statistical analysis explained other relationship with the exception of a lineality and interaction among mechanical properties. Comparing the statistical analysis, the ANFIS was an effective tool to explain human's non-linear perceptions and their interactions. But to apply ANFIS to human's perceptions more effectively, it is necessary to discriminate effective input variables through controlling the properties of samples.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.81-97
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• 2003

In this paper, we suggest a method of robust watermarking for protection of multimedia data using the wavelet transform and artificial neural network. for the purpose of implementation, we decompose a original image using wavelet transform at level 3. After we classify transformed coefficients of other subbands using neural network except fur the lowest subband LL$_3$, we apply a calculated threshold about chosen cluster as the biggest. We used binary logo watermarks to make sure that it is true or not on behalf of the Gaussian Random Vector. Besides, we tested a method of dual watermark insertion and extraction. For the purpose of implementation, we decompose a original image using wavelet transform at level 3. After we classify transformed coefficients of other subbands using neural network except for the lowest subband LL$_3$, we apply a above mentioned watermark insert method. In the experimental results, we found that it has a good quality and robust about many attacks.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3530-3538
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• 1999

In this paper, we propose a novel method for feature extraction of off-line handwritten characters recognition based on human optical neural field model. The proposed feature extraction system divide into three parts ; 1) smoothing process, 2) removing boundaries(boundary lines), 3) extracting feature information. The proposed system first removes rough pixels which are easy to occur in handwritten characters. The system then extracts and removes the boundary information which have no influence on characters recognition. Finally, the feature information for off-line handwritten characters recognition is extracted. With PE2 Hangul database, we perform feature extraction experiments for off-line handwritten characters recognition. In the experiment results, the proposed system based on optical neural field shows that can extract the feature information of off-line handwritten characters including curve lines, circles, quadrangles and so on.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.188-191
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• 2004

야간에 비디오카메라로 촬영시 열악한 주위 환경과 영상 전송에 기인하여 다양한 잡음에 의하여 왜곡되거나 흐린 저대비(low contrast)영상을 가질 수 있다. 본 논문에서는 획득한 저대비 영상을 대비 향상시켜주는 기법을 제안한다. 동영상 압축표준인 MPEG-2는 인간의 시각 특성상 색차(chrominance)신호보다 밝기(luminance)신호에 더 민감하기 때문에 밝기신호와 색차 신호를 분리하여 압축한다. 밝기신호만을 추출한 후 K-means 알고리듬을 사용하여 교차점을 자동으로 선정하는 방법을 사용하는데, 이 최적의 교차점을 선정하는 과정은 획득한 영상을 물체와 배경으로 분리하는 두 개의 클래스 문제로 보고 K-means 알고리듬을 적용하였고 구한 교차점을 사용하여 영상을 양분하여 히스토그램 평활화 방법을 적용하였다 븐 논문에서는 퍼지성 지수(index of fuzziness)를 사용하여 향상의 정도를 측정하였다. 제안된 기법을 저대비 영상에 적용하였으며 그 결과를 히스토그램 평활화 기법의 결과와 비교하였다.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1865-1866
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• 2008

현재 대부분의 멀티미디어 콘텐츠들은 음성 및 영상 정보로 구성되어 있어, 정보 전달 과정에서 정보를 받아들이는 사람에 따라 임의적으로 해석하거나, 수신하는 사람에 따라 편차가 발생할 수 있다. 그러나, 우리 인간에게 가장 명확한 정보 전달 방법은 문자를 이용하여 시각적으로 정보를 제공하는 것이다. 따라서 비디오 및 오디오 정보의 정보 전달 편차 단점 보완을 위한 문자정보를 자유롭게 추가할 수 있다면 기존의 다양한 멀티미디어 콘텐츠의 전달하고자 하는 정보를 가장 완전하고 명확한 전달 서비스 품질을 보장할 수 있다. 본 논문에서는 다양한 멀티미디어 콘텐츠 정보를 정확하고 명확하게 전달할 수 있도록, 디스플레이 장치에 동영상과 문자정보 및 심볼화 정보를 가장 적합한 비율로 정보 전달영역을 설정하고 정보 전송이 가능한 멀티미디어 정보 디스플레이 시스템(MIDS)을 설계하고 구현하였다.