• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.297-300
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• 2006

카오스 로봇의 하드웨어 구현에서 로봇의 차제 또는 바퀴가 정확하기 자기 위치를 인식하고 지시한 방향과 거리만큼 이동하는 것이 가장 중요하다. 본 논문에서는 방위 측정용으로 사용한 마그네틱 자이로센서를 대체한 새로운 각속도 센서를 사용하여 자기 위치 보정 능력 을 향상시키고 정확한 방향을 움직일 수 있는 카오스 로봇을 설계하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.4
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• pp.321-326
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• 2016

In this paper, we propose a luminance correction algorithm based on measuring position for potable luminance measurement system. Measurement position and angle have an affect on the luminance value. We improve the position-based luminance measurement system using luminance correction algorithm based on the measuring angle. We analyze change of luminance value according to the measurement distance and angle from camera and light source. The certified point-luminance meter is used to evaluate a scene luminance measuring method using the image information of camera. Also, we derive an expression equation for evaluating luminance value from determined position. The performances of the proposed system are verified by using comparative experiments with the point-luminance meter using experimental signboard.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.79-86
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• 2009

This study proposed a method of detecting the facial area by calculating Euclidian distances among skin color elements and extracting the characteristics of the face. The proposed algorithm is composed of light calibration and face detection. The light calibration process performs calibration for the change of light. The face detection process extracts the area of skin color by calculating Euclidian distances to the input images using as characteristic vectors color and chroma in 20 skin color sample images. From the extracted facial area candidate, the eyes were detected in space C of color model CMY, and the mouth was detected in space Q of color model YIQ. From the extracted facial area candidate, the facial area was detected based on the knowledge of an ordinary face. When an experiment was conducted with 40 color images of face as input images, the method showed a face detection rate of 100%.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.345-358
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• 2002

DGPS(Differential Global Positioning System) and RTK(Real time Kinematic) are in one of today's most widely used surveying techniques. However surveying with these techniques is restricted by the distance between reference and rover station, and it is difficult to process data in realtime by their own organizational limitation in precise measurement of positioning. To meet these new demands, in this paper, new DGPS and RTK correction data services through the Internet and PSTN(Public Switched Telephony Network) have been proposed. For this purpose, a DGPS and RTK error correction data transmission system is implemented for long-distance using the Internet and PSTN which allows a mobile user at which the rover receiver is located to receive the correction data from the reference in realtime, and analyzed and compared with DGPS and RTK performances by experiments through the Internet and PSTN for the distance and the time.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.3
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• pp.130-140
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• 2024

In this paper, we present a method of applying the kalman filter to control and correct errors in camera sensor recognition depending on the sea state environment. First, the specifications of the ship were described and the degree of error due to rolling was measured. After presenting the distance from the surface of the water to the sidelight required for simulation through PKMR-211, the ship selected as the model, error correction was performed using the camera error value as a variable in the feedback control system. In the experiment, the degree of rolling of the ship was expressed as variables 𝛼 and 𝛽, expressed in angles, and the angle change according to distance was compared. When comparing the error before and after applying the kalman filter in sea state 4, it decreased from +1.5556° to -1.1544° in red light regardless of distance, and the same result was confirmed in green light. Through this, calculations were performed considering the movement of the ship according to the maritime environment, and the future maneuverability of the ship was presented after error correction.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.175-182
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• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.3
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• pp.323-332
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• 2012

An airborne LiDAR system performs several observations on flight routes to collect data of targeted regions accompanying with discrepancies between the collected data strips of adjacent routes. This paper aims to present an automatic error correction technique using modified ICP as a way to remove relative errors from the observed data of strip data between flight routes and to make absolute correction to the control data. A control point data from the existing digital topographic map were created and the modified ICP algorithm was applied to perform the absolute automated correction on the relatively adjusted airborne LiDAR data. Through such process we were able to improve the absolute accuracy between strips within the average point distance of airborne LiDAR data and verified the possibility of automation in the geometric corrections using a large scale digital map.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.371-377
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• 2007

Ionospheric time delay is one of the main error source for single-frequency DGPS applications, including time transfer and Wide Area Differential GPS (WADGPS). Grid-based algorithm was already developed for WADGPS but that algorithm is not applicable to geomagnetic storm condition in accuracy and management. In geomagnetic storm condition, the spatial distribution of vertical ionospheric delay is noisy and therefore the accuracy of modeling become low in grid-based algorithm. For better accuracy, function based algorithm can be used but the continuity of correction message is not guranteed. In this paper, we propose the ionospheric model using wavelet based algorithm. This algorithm shows better accuracy with the same number of correction message than the existing spherical harmonics algorithm and guarantees the continuity of correction messages when the number of message is expanded for geomagnetic storm condition.

• Geophysics and Geophysical Exploration
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• v.20 no.4
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• pp.232-240
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• 2017

Normal moveout correction is one of the main procedures of seismic reflection data processing and a crucial pre-processing step for AVO analysis. Unfortunately, stretch phenomenon, which is the intrinsic problem of NMO correction, degrades the quality of stack section and reliability of AVO analysis. Although muting is applied to resolve this problem, it makes far-offset traces more useful to develop an advanced NMO correction technique without stretch. In this paper, easy and detailed explanations are provided on the definition and methodology of NMO correction, and then the cause of stretch is explained with its characteristics. A graphical explanation for NMO correction is given for the intuitive understanding of stretch phenomenon. Additionally, the theoretical formulation is derived to quantitatively understand the NMO correction. Through explaining the muting process to remove NMO stretch, the limitations of conventional methods are investigated and the need for a new resolution comes to discussion. We describe a stretch-free NMO correction based on inverse theory among many different stretch-free NMO corrections. Finally, the stretch-free NMO correction is verified through synthetic example and real data.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.85-92
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• 2023

Respiratory infections such as COVID-19 mainly occur within enclosed spaces. The presence or absence of abnormal symptoms of respiratory infectious diseases is judged through initial symptoms such as fever, cough, sneezing and difficulty breathing, and constant monitoring of these early symptoms is required. In this paper, image matching correction was performed for the RGB camera module and the thermal imaging camera module, and the temperature of the thermal imaging camera module for the measurement environment was calibrated using a blackbody. To detection the target recommended by the standard, a deep learning-based object recognition algorithm and the inner canthus recognition model were developed, and the model accuracy was derived by applying a dataset of 100 experimenters. Also, the error according to the measured distance was corrected through the object distance measurement using the Lidar module and the linear regression correction module. To measure the performance of the proposed model, an experimental environment consisting of a motor stage, an infrared thermography temperature screening system and a blackbody was established, and the error accuracy within 0.28℃ was shown as a result of temperature measurement according to a variable distance between 1m and 3.5 m.