• Journal of Sensor Science and Technology
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• v.11 no.5
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• pp.255-262
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• 2002

Human retina is able to detect the edge of an object effectively. We designed a CMOS vision chip by modeling cells of the retina as hardwares involved in edge detection. There are several fluctuation factors which affect characteristics of MOSFETs during CMOS fabrication process and this effect appears as output offset of the vision chip which is composed of pixel arrays and readout circuits. The vision chip detecting edge information from input image is used for input stage of other systems. Therefore, the output offset of a vision chip determine the efficiency of the entire performance of a system. In order to eliminate the offset at the output stage, we designed a vision chip by using CDS(Correlated Double Sampling) technique. Using standard CMOS process, it is possible to integrate with other circuits. Having reliable output characteristics, this chip can be used at the input stage for many applications, like targe tracking system, fingerprint recognition system, human-friendly robot system and etc.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.78-84
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• 2015

Depth estimation is often required for robot vision, 3D modeling, and motion control. Previous method is based on the focus measures which are calculated for a series of image by a single camera at different distance between and object. This method, however, has disadvantage of taking a long time for calculating the focus measure since the mask operation is performed for every pixel in the image. In this paper, we estimates the depth by using the focus measure of the boundary pixels located between the objects in order to minimize the depth estimate time. To detect the boundary of an object consisting of a straight line and a circle, we use the Hough transform and estimate the depth by using the focus measure. We performed various experiments for PCB images and obtained more effective depth estimation results than previous ones.

• Journal of Korea Multimedia Society
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• v.12 no.2
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• pp.231-243
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• 2009

Currently interests of embedded software in various areas such as automotive field, ship field, robot field is increasing according to expand market of embedded systems. Various researches such as embedded operating systems, embedded software modeling technique, embedded software testing, and so on are going in progress. However systematic engineering approach in embedded system development is poor because embedded areas focus on hardware parts until now. Furthermore, framework-based de sign technique considering reusability is not reflected in embedded system development. Those development results in many of dead codes scattered in system, and results in poor reusability of system. This paper suggests a framework of embedded system for reusability and a static meta-model for reuse framework. Proposed meta-model expresses not only the structure of reuse framework, but also allows a designer to extend and design easily models of embedded system based on reuse framework according to various embedded system types.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.335-347
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• 2018

The purpose of this study was to find more effective mental health intervention for school based intervention with mental health problem in an elementary school. A systematic review was conducted according to the PRISMA checklist. We accessed databases including RISS, KISS, and the National Assembly Library of Korea. Subject studies were classified according to type of intervention, subject characteristic, and evaluation. Finally, twenty-five studies matched the inclusion criteria. According to types of intervention, it was classified into four types which are psychoeducation(self-management skills, social skills, social emotional learn ing), behavior intervention(positive behavior support, modeling), psychotherapy(art therapy, counseling and parent coaching), and recreation intervention(robot intervention, horticultural therapy). The most of subjects were intellectual disability, the following subjects were ADHD. The most areas of evaluation were emotional change and attention. The findings of this review support school based intervention and provide evidence. And it can be used as an important basic data for preparing more effective mental health-related school-based interventions.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.165-172
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• 1998

The electromechanical energy conversion conditioning and processing implementation in USM direct motion control system is generally divided into two power stages: the two-phase high-frequency ac power inversion stage for driving piezoelectric ceramic PZT transducer array off the USM stator and the mechanical thrust power conversion stage based on the frictional force between the piezo electric stator array and the rotary slider of the USM. However, the dynamic and steady-state mathematical modeling of the USM is extremely default from a theoretical point of view because it contains many complicated an nonlinear characteristics dependant on operation temperature. In +2$0^{\circ}C$~3$0^{\circ}C$, the operating characteristics of the USM has represented normal condition. But the other temperature, it has abnormal condition so that driving frequency, current and motor speed will be down. The recent USM has controller without temperature compensation. This study represents the fuzzy controller for speed compensation according to operating temperature by driving frequency.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.299-308
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• 2014

Various literatures related computing of information processing have been recently shown the researches inspired from the remarkably excellent human capabilities which recognize and categorize very complex visual patterns such as body motions and facial expressions. Applied from human's outstanding ability of perception, the classification function of visual sequences without context information is specially crucial task for computer vision to understand both the coding and the retrieval of spatio-temporal patterns. This paper presents a biological process based action recognition model of computer vision, which is inspired from visual information processing of human brain for action recognition of visual sequences. Proposed model employs the structure of neural fields of bio-inspired visual perception on detecting motion sequences and discriminating visual patterns in human brain. Experimental results show that proposed recognition model takes not only into account several biological properties of visual information processing, but also is tolerant of time-warping. Furthermore, the model allows robust temporal evolution of classification compared to researches of action recognition. Presented model contributes to implement bio-inspired visual processing system such as intelligent robot agent, etc.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.383-388
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• 2005

Depth recovery in robot vision is an essential problem to infer the three dimensional geometry of scenes from a sequence of the two dimensional images. In the past, many studies have been proposed for the depth estimation such as stereopsis, motion parallax and blurring phenomena. Among cues for depth estimation, depth from lens translation is based on shape from motion by using feature points. This approach is derived from the correspondence of feature points detected in images and performs the depth estimation that uses information on the motion of feature points. The approaches using motion vectors suffer from the occlusion or missing part problem, and the image blur is ignored in the feature point detection. This paper presents a novel approach to the defocus technique based depth from lens translation using sequential SVD factorization. Solving such the problems requires modeling of mutual relationship between the light and optics until reaching the image plane. For this mutuality, we first discuss the optical properties of a camera system, because the image blur varies according to camera parameter settings. The camera system accounts for the camera model integrating a thin lens based camera model to explain the light and optical properties and a perspective projection camera model to explain the depth from lens translation. Then, depth from lens translation is proposed to use the feature points detected in edges of the image blur. The feature points contain the depth information derived from an amount of blur of width. The shape and motion can be estimated from the motion of feature points. This method uses the sequential SVD factorization to represent the orthogonal matrices that are singular value decomposition. Some experiments have been performed with a sequence of real and synthetic images comparing the presented method with the depth from lens translation. Experimental results have demonstrated the validity and shown the applicability of the proposed method to the depth estimation.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.180-189
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• 2009

Currently, most automobile companies are interested in research on intelligent autonomous vehicle. They are mainly focused on driver's intelligent assistant and driver replacement. In order to develop an autonomous vehicle, lateral and longitudinal control is necessary. This paper presents a lateral and longitudinal control system for autonomous vehicle that has only mono-vision camera. For lane detection, we present a new lane detection algorithm using clothoid parabolic road model. The proposed algorithm in compared with three other methods such as virtual line method, gradient method and hough transform method, in terms of lane detection ratio. For adaptive control, we apply a vanishing point estimation to fuzzy control. In order to improve handling and stability of the vehicle, the modeling errors between steering angle and predicted vanishing point are controlled to be minimized. So, we established a fuzzy rule of membership functions of inputs (vanishing point and differential vanishing point) and output (steering angle). For simulation, we developed 1/8 size robot (equipped with mono-vision system) of the actual vehicle and tested it in the athletics track of 400 meter. Through the test, we prove that our proposed method outperforms 98 % in terms of detection rate in normal condition. Compared with virtual line method, gradient method and hough transform method, our method also has good performance in the case of clear, fog and rain weather.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.7
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• pp.700-710
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• 2009

A computer vision technique of estimating the location of an unmanned ground vehicle is proposed. Identifying the location of the unmaned vehicle is very important task for automatic navigation of the vehicle. Conventional positioning sensors may fail to work properly in some real situations due to internal and external interferences. Given a DSM(Digital Surface Map), location of the vehicle can be estimated by the registration of the DSM and multiview range images obtained at the vehicle. Registration of the DSM and range images yields the 3D transformation from the coordinates of the range sensor to the reference coordinates of the DSM. To estimate the vehicle position, we first register a range image to the DSM coarsely and then refine the result. For coarse registration, we employ a fast random sample matching method. After the initial position is estimated and refined, all subsequent range images are registered by applying a pair-wise registration technique between range images. To reduce the accumulation error of pair-wise registration, we periodically refine the registration between range images and the DSM. Virtual environment is established to perform several experiments using a virtual vehicle. Range images are created based on the DSM by modeling a real 3D sensor. The vehicle moves along three different path while acquiring range images. Experimental results show that registration error is about under 1.3m in average.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.4
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• pp.37-45
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• 2000

In this paper we suggest a method of detecting the two eyes position of moving viewer by using images obtained through a color CCD camera, and also a method of rendering view-dependent 3D image which consists of depth estimation, image-based 3D object modeling and stereoscopic display process. Through the experiment of applying the suggested methods, we could find the accurate two-eyes position with the success rate of 97.5% within the processing time of 0.39 second using personal computer, and display the view-dependent 3D image using Fl6 flight model. And through the similarity measurement of stereo image rendered at z-buffer by Open Inventor and captured by stereo camera using robot, we could find that view-dependent 3D picture obtained by our proposed method is optimal to viewer.