• Journal of the Institute of Convergence Signal Processing
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• v.10 no.4
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• pp.233-238
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• 2009

In this paper, we propose the methods to select the stable region for the detect region which is required in the system used the face to the ROI in the auto-focus digital camera. this method regards the face region as the ROI in the progressive input frame and focusing the region in the mobile camera embeded ISP module automatically. The learning algorithm to detect the face is the Adaboost algorithm. we proposed the method to detect the slanted face not participate in the train process and postprocessing method for the results of detection, and then we proposed the stabilization method to sustain the region not shake for the region. we estimated the capability for the stabilization algorithm using the RMS between the trajectory and regression curve.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.709-714
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• 2017

The curved panel is widely used for display of TVs and smart phones. This paper proposes a new auto-focusing method for curved panel inspection system. Since the distance between the camera and the panel varies with the curve position, the camera should change its focus at every inspection time. In order to reduce the focusing time, we propose an effective focusing method that considers the mathematical model of panel curve. The Lagrange polynomial equation is applied to modeling the panel curve. The foci of initial three points are used to get the curve equation, and the other foci are calculated automatically from the curve equation. The experiment result shows that the proposed method can reduce the focusing time.

• Proceedings of the Korean Society of Laser Processing Conference
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• 2006.06a
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• pp.123-128
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• 2006

We constructed a micro-patterning system that build patterns on a photoresist coated wafer using laser direct writing system. Confocal microscope system was adapted for real-time auto-focusing of the laser writing lens to generate lines of uniform width.

• Korean Journal of Optics and Photonics
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• v.22 no.1
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• pp.10-15
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• 2011

In this paper, we propose an auto-focusing algorithm which extracts a depth parameter by analyzing a selected part of a hologram, and we use experimental results to show that the algorithm is practical. First, we record a complex hologram using Optical Scanning Holography. Next we select some part of hologram and extract depth information through Gaussian low pass filtering, synthesizing a real-only hologram, power fringe-adjusted filtering and inverting to a new frequency axis. Finally, we reconstruct the hologram automatically using the extracted depth location.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.10
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• pp.377-382
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• 2018

This study deals with internal state and tissue density analysis methods for red ginseng grade determination. For internal measurement of red ginseng, there have been various studies on nondestructive testing methods since the 1990s, It was difficult to grasp the most important inner hole and inside whites in the grading. So in this study, we developed a closed capturing device for infra-red illumination environment, and developed an internal measurement system that can detect the presence and diameter of inner hole and inside whites. Made devices consisted of infrared lights with a high transmission rate of red ginseng in 920 nanometer wave band, a infra-red camera and a Y axis actuator with a red ginseng automatically controlled focus on the camera. The proposed algorithm performs an auto-focus system on the Y-axis actuator to automatically adjust the sharp focus of the object according to the size and thickness. Then red ginseng is rotated $360^{\circ}$ at $1^{\circ}$ intervals and 360 total images are acquired, and reconstructed as a sinogram through Radon transform and Back-projection algorithm was performed to acquire internal images of red ginseng. As a result of the algorithm, it was possible to acquire internal cross-sectional image regardless of the thickness and shape of red ginseng. In the future, if more than 10,000 different shapes and sizes of red ginseng internal cross-sectional image are acquired and the classification criterion is applied, it can be used as a reliable automated ginseng grade automatic measurement method.

• Journal of radiological science and technology
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• v.36 no.2
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• pp.111-122
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• 2013

This study was carried out to reduce patient dose through focus-detector distance, kilovoltage, and a combination of copper filters. In the C, L-spine lateral, Skull AP views were obtained by making changes of 60-100 kV in tube voltage and of 100-200 cm in focus-detector distance and by adding a copper filter when using an auto exposure control device in the digital radiography equipment. The incident dose showed 90 kV, 0.3 mmCu in C-spine lateral with 0.06 mGy under the condition of 200 cm; 100 kV, 0.3 mmCu with 0.40 mGy under the condition of 200 cm and 90 kV 0.3 mmCu in Skull AP with the lowest value of 0.24 mGy under the condition of 140 cm. It was observed that entrance surface dose decreased the most when was increased by 150 cm, 70 kV (C-spine lateral), 81 kV (L-spine lateral). It was also found out that as the between the focus-detector increased in the expansion of the video decreased but the difference was not significant when the distance was 180 cm or more. Skull AP showed the most reduction in the entrance surface dose when the tube voltage was changed by 80 kV, 0.1 mmCu, and 120 cm. Therefore, when using the automatic exposure control device, it is recommended to use the highest tube voltage if possible and to increase focus-detector distance at least by 150~200 cm in wall and 120~140 cm in table in consideration of the radiotechnologist's physical conditions, and to combine 0.1~0.3 mmCu and higher filters. It is thus expected to reduce patient dose by avoiding distortion of images and reducing the entrance surface dose.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.3078-3080
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• 2005

본 논문에서는 AF 기능을 구현함에 있어서 2 백만 화소 카메라 모듈인 Sharp LZ0P3731의 기능, AF 모터 (VCM, Voice Coil Motor)에 작용하는 힘과 구동원리, 이를 구동하기 위한 H/W의 설계 특성, 및 DM270을 이용한 AF 제어 시 Focus Value의 특성 분석을 바탕으로 Focus Value 특성을 고려한 최적 AF 알고리즘을 개발하였다. 본 논문에서 제안한 최적 AF 알고리즘은 '최대의 Focus Value가 각 State의 Step Value 마다 각각 다른 위치에서 검출'되는 AF 모터 및 구동 H/W특성을 고려하여, 최적 AF 기능은 최대의 AF Value에 근접하는 Lens Position 제어가 가능하도록 하였다. 이를 검증하기 위한 윈도우용 S/W로 성능을 확인한 결과, 일반적인 AF 기능은 58 프레임으로 3.87초의 시간이 소요되는 반면, 제안한 AF 기능은 25 프레임으로 1.67초로 2배 이상의 빠른 AF 성능을 가졌다.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.83.2-83.2
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• 2013

Camera for QUasars in EArly uNiverse (CQUEAN) is an optical CCD camera developed by the Center for the Exploration of the Origin of the Universe (CEOU). In 2010 August, CQUEAN was attached on the 2.1m Otto Struve Telescope at the McDonald Observatory in Texas, USA. As the main purpose of CQUEAN is detecting the Lyman breaks of redshift ~5 quasars, it is sensitive to near-infrared wavelengths (0.7-1.0 ${\mu}m$). For the auto-guiding system, it is using a rotating guide arm to find guide stars on the Cassegrain off-axis focus of the telescope. We plan to upgrade a new filter wheel system consists of a series of narrow band filters. We will install this independent auto-guiding units on the finder scope, which makes rooms on the Cassegrain focal plane of the main telescope. In this presentation we present the system architecture of the CQUEAN Auto-guiding Package (CAP).

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.13-16
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• 2006

사진을 찍을 때 카메라는 보기 좋은 사진을 얻을 수 있도록 많은 기능을 제공하고 있다. 대표적인 기능으로 자동 초점거리 조정(Auto Focus), 자동 색온도 보정(Auto White Balance), 자동 노출 조정(Auto Exposure)이 있다. 본 논문에서는 편리한 기능들 중 하나로써 자동 노출제어 시스템을 구현하였다. 본 논문에서 제안하는 자동 노출제어 시스템은 가변 시상수(Variable Time Constant)를 가지는 IIR 필터를 이용한다. Zone System에서 보여주는 사물의 휘도정보를 바탕으로 하여 이상적인 영상의 휘도 특성 그래프를 얻어내고, 이와 현재의 노출설정에서 휘도와 비교하여 적정 노출을 찾는다. 제안하는 자동 노출제어 시스템은 적정 노출을 얻을 수 있는 위치로 이동하기 위하여 기존의 마이크로 콘트롤러 등을 이용하여 구현하는 방법과 달리 간단한 구성을 가지는 IIR 필터를 이용한다. 제안하는 자동 노출제어 시스템은 간단한 구성을 가지므로 콤팩트 이미지 센서를 구성하기 위하여 사용 할 수 있다.

• The Korean Journal of Applied Statistics
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• v.35 no.5
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• pp.645-655
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• 2022

In this paper, we investigate automatic functions for time series forecasting in R system and compare their performances. For the exponential smoothing models and ARIMA (autoregressive integrated moving average) models, we focus on the representative time series forecasting functions in R: forecast::ets(), forecast::auto.arima(), smooth::es() and smooth::auto.ssarima(). In order to compare their forecast performances, we use M3-Competiti on data consisting of 3,003 time series and adopt 3 accuracy measures. It is confirmed that each of the four automatic forecasting functions has strengths and weaknesses in the flexibility and convenience for time series modeling, forecasting accuracy, and execution time.