• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.1-8
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• 2004

It's a very meaningful experimental study to image restoration of ancient villages vanished at the real life spatial world. Focused on Cheung-Pyung Lake around where most part were flooded by the Chung-Ju large dam founded in early 1980s, we used remote sensing technique in this study in order to restore topographical features before the flood with 3 dimensional effects. It was gathered comparatively good satellite photos and remotely sensed digital images, then its made a new color image from these and the topographical map which had been made before filled water. This task was putting together two kinds of different timed images. And then, we generated DEM(digital elevation model) including the outskirts of that area as harmonizing current contour lines with the map. That could be a perfect 3D image of Cheung-Pyung around before when it had been flood by making perspective images from all directions, north, south, east and west, for showing there in three dimensions. Also, flying simulation we made for close visiting can bring us to experience their real space at that time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.247-253
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• 2019

In this paper, we present a new method for real-time tracking of human walking around a laser sensor system. The method converts range data with $r-{\theta}$ coordinates to a 2D image with x-y coordinates. Then human tracking is performed using human's features, i.e. appearances of human walking pattern, and the input range data. The laser sensor based human tracking method has the advantage of simplicity over conventional methods which extract human face in the vision data. In our method, the problem of estimating 2D positions and orientations of two walking human's ankle level is formulated based on a moving trajectory algorithm. In addition, the proposed tracking system employs a HMM to robustly track human in case of occlusions. Experimental results using a real system demonstrate usefulness of the proposed method.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.148-156
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• 2013

This paper suggests a multi-level and multi-output SMPS based on a shared digital logic controller through independently operating in each dedicated time periods. Although the shared architecture can be devised with small area and high efficiency, it has critical drawbacks that real-time control of each DPWM generators are impossible and its output voltage can be unstable. To solve these problems, a real-time current compensation scheme is proposed as a solution. A current consumption of the core block and entire block with four driver buffers was simulated about 4.9mA and 30mA at 10MHz switching frequency and 100MHz core operating frequency. Output voltage ripple was 11 mV at 3.3V output voltage. Over/undershoot voltage was 10mV/19.6mV at 3.3V output voltage. The noise performance was simulated at 800mA and 100KHz load regulation. Core circuit can be implemented small size in $700{\mu}m{\times}800{\mu}m$ area. For the verification of proposed circuit, the simulations were carried out with Dong-bu Hitek BCD $0.35{\mu}m$ technology.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.74-82
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• 2019

The revolution of industry 4.0 is enabling us to build an intelligent connection society called smart cities. The use of renewable energy in particular solar energy is extremely important for modern society due to the growing power demand in smart cities, but its difficult to monitor and manage in each buildings since need to be deploy low energy sensors and information need to be transfer via wireless sensor network (WSN). The Internet of Things (IoT) / low-power wide-area (LPWA) is an emerging WSN technology, to collect and monitor data about environmental and physical electrical / electronics devices conditions in real time. However, providing power to IoT sensor end devices and other public electrical loads such as street lights, etc is an important challenging role because the sensor are usually battery powered and have a limited life time. In this paper, we proposes an efficient solar energy-based power management scheme for smart city based on IoT technology using LoRa wide-area network (LoRaWAN). This approach facilitates to maintain and prevent errors of solar panel based energy systems. The proposed solution maximizing output the power generated from solar panels system to distribute the power to the load and the grid. In this paper, we proved the efficiency of the proposed system with Simulink based system modeling and real-time emulation.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.269-282
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• 2021

As the distribution of 3D content such as augmented reality and virtual reality increases, the importance of real-time computer animation technology is increasing. However, the computer animation process consists mostly of manual or marker-attaching motion capture, which requires a very long time for experienced professionals to obtain realistic images. To solve these problems, animation production systems and algorithms based on deep learning model and sensors have recently emerged. Thus, in this paper, we study four methods of implementing natural human movement in deep learning model and kinect camera-based animation production systems. Each method is chosen considering its environmental characteristics and accuracy. The first method uses a Kinect camera. The second method uses a Kinect camera and a calibration algorithm. The third method uses deep learning model. The fourth method uses deep learning model and kinect. Experiments with the proposed method showed that the fourth method of deep learning model and using the Kinect simultaneously showed the best results compared to other methods.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.397-406
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• 2012

Objective: The aim of this study is to determine legible Korean font sizes within in-vehicle information systems(IVISs) in diving conditions. Background: Font legibility within IVISs is one of important causes on its' safe operations during driving. Several researches proposed some guidelines on the legible English font sizes within IVISs. On the contrary, appropriate Korean font sizes have been hardly known in spite of the typological differences between English and Korean. Therefore, more systematic researches for improving the legibility on Korean font size within IVISs have been required. Method: In this study, an experiment was performed with the following experimental factors: the existence of vibration, the color contrasts(white on black, black on white), the font types(HDR, CubeR, Gothic), and the font sizes(6, 8, 10, 12, 14, 16, 18, 20, 22, 24pt). To fit the experimental conditions into real driving environments, the illuminance was controlled to 15lx by using LED lamp and the distance between IVIS and participants was kept to 70cm. Moreover, all participants took the shutter glasses for employing well-known occlusion techniques. Results: The experimental results showed that 'HDR' and 'Non-vibration + Black on white' group took the shortest response time, and decreasing slopes of the response time with increasing font sizes were slowing down at 14pt then flattened out at 22pt regardless of the existence of vibration and color contrasts. Conclusion: The minimum size for legible Korean font would be about 14pt(5.47mm) and the optimum size would be about 22pt(8.59mm). Application: The guideline on the Korean font sizes from this study will be applied to design an IVIS in the future.

• Journal of Advanced Navigation Technology
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• v.20 no.6
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• pp.574-579
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• 2016

Unlike general unmanned aerial vehicles, the quad-rotor is attracting the attention of many people because of simple structure and very useful value. However, as the interest in drones increases, the safety and location of vehicles are becoming more important provide against aviation safety accidents or lost accidents. Therefore, in this paper, we propose a tracking system that stabilizes the model with a simple controller by linearized modeling and grasp tilt angle data from various sensor through the filter. The developed tracking system transmits the position of the quad-rotor in flight to the computer and shows it through the route, so it can check the flight path and various information such as flight speed and altitude at the same time. Then the sensor used in the actual quad-rotor can not measure exact sensor data for disturbance and vibration. So we use sensor fusion of Kalman filter and Complementary filter to overcome this problem and the stability of the quad-rotor hovering is realized by PID control. Through simulation, various information such as the speed, position, and altitude of the quad-rotor were confirmed in real time.

• Journal of IKEEE
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• v.18 no.1
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• pp.57-63
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• 2014

This paper is to technically implement the sensing platform for Home-Wellness Robot. The self-Localization of indoor mobile robot is very important for the sophisticated trajectory control. In this paper, the robot's self-localization algorithm is designed by RF sensor network and fuzzy inference. The robot realizes its self-localization, using RFID sensors, through the collaboration algorithm which uses fuzzy inference for combining the strengths of triangulation and triangulation. For the triangulation self-Localization, RSSI is implemented. TOA method is used for realizing the triangulation self-localization. The final improved position is, through fuzzy inference, made by the fusion algorithm of the resultant coordinates from trilateration and triangulation in real time. In this paper, good performance of the proposed self-localization algorithm is confirmed through the results of a variety of experiments in the base of RFID sensor network and reader system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.359-367
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• 2002

In this paper, a new embedded wavelet packet image coder algorithm is proposed for an effective image coder using correlation between partitioned coefficients. This new algorithm presents parent-child relationship for reducing image reconstruction error using relations between individual frequency sub-bands. By parent-child relationship, every coefficient is partitioned and encoded for the zerotree data structure. It is shown that the proposed wavelet packet image coder algorithm achieves low bit rates and rate-distortion. It also demonstrates higher PSNR under the same bit rate and an improvement in image compression time. The perfect rate control is compared with the conventional method. These results show that the encoding and decoding processes of the proposed coder are simpler and more accurate than the conventional ones for texture images that include many mid and high-frequency elements such as aerial and satellite photograph images. The experimental results imply the possibility that the proposed method can be applied to real-time vision system, on-line image processing and image fusion which require smaller file size and better resolution.