• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.109-118
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• 2008

In mapping a texture image into a 3D mesh model for photo-realistic graphic applications, the compression of texture image is as important as geometry of 3D mesh. Typically, the size of the (compressed) texture image of 3D model is comparable to that of the (compressed) 3D mesh geometry. Most 3D model compression techniques are to compress the 3D mesh geometry, rather than to compress the texture image. Well-known image compression standards (i.e., JPEG) have been extensively used for texture image compression. However, such techniques are not so efficient when it comes to compress an image with texture patches, since the patches are little correlated. In this paper, we proposed a preprocessing method to substantially improve the compression efficiency of texture compression. From the experimental results, the proposed method was shown to be efficient in compression with a bit-saving from 23% to 45%.

• ETRI Journal
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• v.32 no.5
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• pp.827-830
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• 2010

For an adaptive cruise control (ACC) stop-and-go system in automotive applications, three radar sensors are needed because two 24 GHz short range radars are used for object detection in an adjacent lane, and one 77 GHz long-range radar is used for object detection in the center lane. In this letter, we propose a single sensor-based 24 GHz radar with a detection capability of up to 150 m and ${\pm}30^{\circ}$ for an ACC stop-and-go system. The developed radar is highly integrated with a high gain patch antenna, four channel receivers with GaAs RF ICs, and back-end processing board with subspace based digital beam forming algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.107-108
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• 2011

A methodology to measure 3-dimensional vibrational displacement of a structure by digital photogrammetry is proposed in this paper. Stereo digital images of a vibrating structure were obtained by two non-metric cameras. Then by applying the collinearity condition to the images, the 3-d displacement time history data of a point or many points can be calculated by the present methodology. Experimental work was performed to measure the displacement time history for a cantilever beam excited by a piezoelectric patch, in which the in-depth displacement data obtained by the proposed method well matched the laser sensor data.

• Korean Journal of Remote Sensing
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• v.13 no.2
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• pp.121-132
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• 1997

This paper describes the development of a stereo matching algorithm for extracting Digital Elevation Model(DEM) from satellite images. This matching algorithm is based on a non-linear least squares correlation estimation but has improved matching speed. The algorithm consists of three steps: matching execution, matching control and matching optimization. Each is described. The performance of the presented algorithm is quantitatively analyzed with experiments on matching probability, matching speed and matching convergence radius.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.16-22
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• 2011

Recently, the use of portable projector expands applications to meeting at fields. Accordingly, the projection is not always guaranteed on white screen, causing some color distortion. Several algorithms have been suggested to correct the projected color on the light colored screen. These have limitation on the use of measurement equipment which can't bring always. In this paper, color correction method using general still camera as convenient measurement equipment is proposed to match the colors between on white and colored screens. A patch containing 9 ramps of each channel are firstly projected on white and colored screens, then captured by the camera, respectively, Next, digital values are obtained by the captured image for each ramp patch on both screens, resulting in different values to the same patch. After that, we check which ramp patch on colored screen has the same digital value on white screen, repeating this procedure for all ramp patches. The difference between corresponding ramp patches reveals the quantity of color shift. Then, color correction matrix is obtained by regression method using matched values. In the experimental results, the proposed method gives better color correction on the objective and subjective evaluation than the previous methods.

• Journal of the Korean Graphic Arts Communication Society
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• v.26 no.1
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• pp.51-64
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• 2008

In this paper, an experiment was done where the input(scanner, digital still camera) and monitor(CRT, LCD) device used the linear multiple regression and the GOG (Gain-Offset-Gamma) characterization model to perform a color transformation. Also to color conversion method of the digital printer it used the LUT(Look Up Table), 3dimension linear interpolation and a tetrahedron interpolation method. The results are as follows. From color reappearance of digital printing case of monitor, the XYZ which it converts in linear multiple regression of input device it multiplied the inverse matrix, and then it applies the inverse GOG model and after color converting the patch of the result most which showed color difference below 5 at monitor RGB value. Also, The XYZ which is transmitted from the case input device which is a printer it makes at LAB value to convert an extreme, when the LAB value which is converted calculating the CMY with the LUT and tetrahedral interpolations the color conversion which considers the black quantity was more accurate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3268-3283
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• 2018

With the advent of the Information Age, the source identification of digital images, as a part of digital image forensics, has attracted increasing attention. Therefore, an effective technique to identify the source of digital images is urgently needed at this stage. In this paper, first, we study and implement some previous work on image source identification based on sensor pattern noise, such as the Lukas method, principal component analysis method and the random subspace method. Second, to extract a purer sensor pattern noise, we propose a sample selection method to improve the random subspace method. By analyzing the image texture feature, we select a patch with less complexity to extract more reliable sensor pattern noise, which improves the accuracy of identification. Finally, experiment results reveal that the proposed sample selection method can extract a purer sensor pattern noise, which further improves the accuracy of image source identification. At the same time, this approach is less complicated than the deep learning models and is close to the most advanced performance.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.215-216
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• 2006

In this paper, the antenna the with linear active phased array of $1{\times}16$ operated in DBS band was designed. The antenna was composed of sixteen radiating elements, sixteen active channels and five Wilkinson power combiners with 4-channel inputs, a digital control board and a stabilizing DC bias board. The radiating element of the array has the structure of a microstrip stack patch with a left-hand circular polarization. And, each active channel consists of a low noise ampilifier, a 3-bit digital phase shifter and a variable analog attenuator. The breadboard of linear active phased array antenna was also fabricated to test the electrical performances. The radiation patterns of the antenna were measured after correcting initial phases of each active channel in aechoic chamber. And also, the beam scanning chracteristcs of $10^{\circ}$, $20^{\circ}$, $30^{\circ}$ were measured.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.7
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• pp.730-736
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• 2013

Time-domain clutter generation model for airborne pulse doppler phase-array radar is presented. Time-domain surface clutter signal is generated assuming earth of a sphere and considering geometry of a clutter patch, and generation of sub-array clutter signal is presented. The generated sub-array clutter signal can be used by simulation input signal in various radar applications of DBF(Digital Beamforming), ABF(Adaptive Beamforming), Stap(Space-Time Adaptive Processing) and etc.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.389-390
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• 2022

본 논문에서는 동물 이미지 분류를 위한 작은 데이터 세트를 기반으로 하는 향상된 딥 러닝 방법을 제안한다. 먼저, CNN을 사용하여 작은 데이터 세트에 대한 훈련 모델을 구축한다. 데이터 증대를 사용하여 훈련 세트의 데이터 샘플을 확장한다. 다음으로, VGG16과 같은 대규모 데이터 세트에서 사전 훈련된 네트워크를 사용하여 작은 데이터 세트의 병목 현상 기능을 추출한다. 그리하여 두 개의 NumPy 파일에 새로운 훈련 데이터 세트 및 테스트 데이터 세트로 저장한다. 마지막으로 완전히 연결된 네트워크를 훈련시킨다.