• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1028-1030
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• 2017

최근 스마트 기기에 대한 관심이 지속적으로 증가함에 따라 다양한 스마트 기기가 출시되고 그에 대한 연구가 활발히 진행되고 있다. 기존 스마트 기기에 탑재된 모션 센서에 관한 연구 대부분은 사용자의 움직임을 이용한 게임 연구에 치우쳐 있다. 본 논문은 사용자 모션의 시각화라는 접근을 통해 사용자의 모션을 직관적으로 볼 수 있도록 하였다. 안드로이드 기반 모바일 기기에 탑재되어 있는 모션 센서 중 방향 센서를 이용하여 사용자 모션에 대한 데이터를 수집하고 이를 시각화 알고리즘을 통해 시각화 한다. 시각화한 결과를 손 글씨 숫자 이미지의 대형 데이터베이스 기반 머신러닝을 활용하여 분석하고 사용자의 모션을 인식할 수 있다는 결과를 확인했다.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.283-288
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• 2024

In this paper, a novel mechanism for overcoming obstacles is studied by designing an All-Directional RC car for obstacle traversal and creating test courses with various obstacles. We propose an algorithm for controlling the RDS3115 servo motor and utilize a gyro sensor to detect the incline of various obstacle terrains, adjusting the servo motor's angle to enable the RC car to navigate the terrain. Through terrain experiments in the test course, we determined the most suitable RC car turning angles for traversing all obstacle terrains created in the experimental terrain.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.227-233
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• 2018

In recent years, connected car, which has sensors and computers attached to vehicles used to detect the surrounding environment, has been actively studied. However, in order to configure the connected car environment, various sensors and roadside equipments are required to detect the surrounding environment of the vehicle, and also communication techniques for transmitting the collected data are in demands. Therefore, in this paper, the mobile virtual fence that collects and communicates the data of the surrounding environment through the sensor mounted on the mobile device is applied to the vehicles that were released before the connected car service environment was constructed, We propose a mechanism to receive the service and show the possibility through experiment.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.1
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• pp.114-120
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• 2013

Recently, navigation systems based on wireless communication have been applied to the internal structures such as building or ship. If a stable azimuth information is obtained, these systems can effectively guide the direction of the user's progress through the information and then can improve the performance of guidance. Since conventional method which has acquired an azimuth information using geomagnetic and acceleration sensor(azimuth sensor hereafter) is sensitive to the effects of the magnetic field, it has unstable error range according to the surrounding environment. In order to improve these problems, this paper presents a new relative azimuth estimation algorithm using the displacement of a mobile node and its rotation angle based on Wireless communication. For the performance assessment of the proposed algorithm, experiments using rotating arm are performed and the results are confirmed that the proposed system can estimate the relative azimuth without using additional sensors.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.19-26
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• 2019

In this paper, the classification performance of learning algorithms is compared for TAB digit recognition. The TAB digits that are segmented from TAB musical notes contain TAB lines and musical symbols. The labeling method and non-linear filter are designed and applied to extract fret digits only. The shift operation of the 4 directions is applied to generate more data. The selected models are Bayesian classifier, support vector machine, prototype based learning, multi-layer perceptron, and convolutional neural network. The result shows that the mean accuracy of the Bayesian classifier is about 85.0% while that of the others reaches more than 99.0%. In addition, the convolutional neural network outperforms the others in terms of generalization and the step of the data preprocessing.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.359-370
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• 2007

Lane tracking and obstacle avoidance are considered two of the key technologies on an unmanned ground vehicle system. In this paper, we propose a method of lane tracking and obstacle avoidance, which can be expressed as vehicle control, modeling, and sensor experiments. First, obstacle avoidance consists of two parts: a longitudinal control system for acceleration and deceleration and a lateral control system for steering control. Each system is used for unmanned ground vehicle control, which notes the vehicle's location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacle and perform obstacle avoidance on the road, which involves vehicle velocity. Second, we explain a method of lane tracking by means of a vision system, which consists of two parts: First, vehicle control is included in the road model through lateral and longitudinal control. Second, the image processing method deals with the lane tracking method, the image processing algorithm, and the filtering method. Finally, in this paper, we propose a method for vehicle control, modeling, lane tracking, and obstacle avoidance, which are confirmed through vehicles tests.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.860-867
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• 2003

In this paper, an efficient core point detection method using orientation pattern labeling is proposed in fingerprint image. The core point, which is one of the singular points in fingerprint image, is used as the reference point in the most fingerprint recognizing system. Therefore, the detection of the core point is the most essential step of the fingerprint recognizing system, it can affect in the whole system performance. The proposed method could detect the position of the core point by applying the labeling method for the directional pattern which is come from the distribution of the ridges in fingerprint image and applying detailed algorithms for the decision of the core point's position. The simulation result of proposed method is better than the result of Poincare index method and the sine map method in executing time and detecting rate. Especially, the Poincare index method can't detect the core point in the detection of the arch type and the sine map method takes too much times for executing. But the proposed method can overcome these problems.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.53-59
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• 2011

In many face recognition applications such as security systems, it is assumed that upright faces are given to the system. In order for the system to be used in more general environments, the system should be able to deal with the rotated faces properly. It is a generally used approach to rotate the face detection window and apply face detector repeatedly to detect a rotated face in the given image. But such an approach requires a lot of computation time. In this paper, a method of extracting the axis of symmetry for a given set of points is proposed. The axis of symmetry for the edge points in the face detection window is extracted in a way that is fast and accurate, and the face detector is applied only for that direction. It is shown that the mean and standard deviation of the symmetry detection error is $0^{\circ}$ and $3^{\circ}$ respectively, for the database used.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.135-140
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• 2014

As the digital image devices are widely used, interests in the software- and the hardware-related image processing become higher and the image processing techniques are applied in various fields such as object recognition, object detection, fingerprint recognition, and etc. For the edge detections Sobel, Prewitt, Laplacian, Roberts and Canny detectors are used and these existing methods can excellently detect the edges of the images without noise. However, in the images corrupted by the impulse noise, these methods are insufficent in noise elimination characteristics, showing unsatisfactory edge detection. Therefore in this paper, in order to obtain excellent edge detection characteristics in the corrupted image by the impulse noise, an detection algorithm is porposed, which uses the central pixel of mask divided by four regions along the axis, calculates the estimated mask according to the representing pixel values in each regions, and detects the final edges by applying the estimates mask and the new directional one.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.1001-1010
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• 2021

Normal people are not deeply aware of their dependence on sight when eating. However, since the visually impaired do not know what kind of food is on the table, the assistant next to them holds the blind spoon and explains the position of the food in a clockwise direction, front and rear, left and right, etc. In this paper, we describe the development of a meal assistance system that recognizes each food image and announces the name of the food by voice when a visually impaired person looks at their table using a smartphone camera. This system extracts the food on which the spoon is placed through the YOLO model that has learned the image of food and tableware (spoon), recognizes what the food is, and notifies it by voice. Through this system, it is expected that the visually impaired will be able to eat without the help of a meal assistant, thereby increasing their self-reliance and satisfaction.