• The Optical Journal
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• s.129
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• pp.65-69
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• 2010

렌즈들의 고유한 초점거리는 모두 대각선 방향의 화각을 표시한 것으로 화각은 말 그대로 화면을 담을 수 있는 각도를 말한다. 화각이 제일 넓은 렌즈는 물고기가 바라보는 것과 같다고 해서 붙여진 어안렌즈를 비롯하여 광각렌즈, 망원렌즈 등이 있다. 이번호에서는 표준렌즈, 망원렌즈, 광각렌즈 등을 통해 초점 거리별 렌즈의 활용법을 알아보자.

• Korean Journal of Optics and Photonics
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• v.23 no.5
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• pp.179-188
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• 2012

Lenses with an ultra wide angle of view are usually called fisheye lenses since a fish can see an ultra wide panoramic view under water. As the angle of view for these kinds of lenses reaches a wide angle, the illumination on an image sensor is reduced by a rapid drop. In this paper, we discuss the causes and the ways to correct for a rapid drop. First, it is treated for the sign convention of directional cosine vectors and normal vectors on the curved surface by means of analytic geometry. And, from the fundamental discussion for these vectors, the rapid illumination drop is numerically analyzed for various kinds of causes by utilizing geometrical optics and radiometry as well as Fresnel equations derived from electromagnetic boundary conditions. As a result, we are able to get the full understanding for the rapid illumination drop and to propose ways to correct effects due to an wide angle of view.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.3
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• pp.323-330
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• 2009

The demand that we are monitoring security and crime of the urban facilities is increasing recently, but the using CCTV devices are expensive. In this research, we enlarge the angle of view using the Fish-eye Lens and the Photogrammetry, the efficiency of monitoring enhance. First, we carry out the calibration of the Fish-eye Lens indoors, we calculate the correction parameters, and then covert the original image-point to new image-point correcting distortion. Second, the correction program with the correction parameters can obtain the real-time correcting image. Lastly, for authorization the developed program we compare correcting-image with scanning-imge, it is showed the RMSE is 3.2pixel.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.633-634
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• 2022

본 논문에서는 비행 시간 측정(TOF) 센서와 동일한 View로 고정되고 차량의 진행 방향으로 수평 설치 가능한 카메라를 연구 개발한다. 이 카메라는 객체 인식 정확도 향상을 위하여 1,280×720 해상도 적용하고 30fps로 영상을 출력하며 180°이상의 광각 어안렌즈를 적용하는 것이 가능도록 한다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.2
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• pp.103-110
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• 2008

General lens, widely using in Photogrammetry, has narrow view, and have to adjust "Image-Registration Method" after obtain images and it need cost; economic, period of time. Recent days, there is various study that use wide-angle lens, usually for robotics field, put to practical use in photogrammetry instead of general lens. In this studies, distortion tendency of wide-angle lens and utilize the correction techniques suitable to wide-angle lens by the existing photographic survey methods. After carrying out the calibration of the wide-angle lens, we calculated the correction parameters, and then developed the method that convert the original image-point to new image-point correcting distortion. For authorization the developed algorithm, we had inspection about shape and position; there are approximately 2D RMSE of 3 pixel, cx = 2, and cy = 3 different.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.11-19
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• 2013

This paper presents a simple method to estimate center of distortion and correct radial distortion from fish-eye lens. If the center of image is not locate that of lens in a straight line, the disadvantage of FOV model is low accurate because of correcting distortion without estimated centre of distortion. We propose a method accurately estimating Distortion center using FOV model and 2D pattern from wide angle lens. Our method determines the center of distortion in least error between straight lines and curves with FOV model. The results of experimental measurements on synthetic and real data are presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.672-673
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• 2022

In this paper, we discuss a camera that is fixed in the same view as the TOF sensor and can be installed horizontally in the vehicle's moving direction. This camera applies 1280×720 resolution to improve object recognition accuracy, outputs images at 30fps, and can apply a wide-angle fisheye lens of 180° or more.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.1
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• pp.96-110
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• 2017

Most of vehicle detection studies using the existing general lens or wide-angle lens have a blind spot in the rear detection situation, the image is vulnerable to noise and a variety of external environments. In this paper, we propose a method that is detection in harsh external environment with noise, blind spots, etc. First, using a fish-eye lens will help minimize blind spots compared to the wide-angle lens. When angle of the lens is growing because nonlinear radial distortion also increase, calibration was used after initializing and optimizing the distortion constant in order to ensure accuracy. In addition, the original image was analyzed along with calibration to remove fog and calibrate brightness and thereby enable detection even when visibility is obstructed due to light and dark adaptations from foggy situations or sudden changes in illumination. Fog removal generally takes a considerably significant amount of time to calculate. Thus in order to reduce the calculation time, remove the fog used the major fog removal algorithm Dark Channel Prior. While Gamma Correction was used to calibrate brightness, a brightness and contrast evaluation was conducted on the image in order to determine the Gamma Value needed for correction. The evaluation used only a part instead of the entirety of the image in order to reduce the time allotted to calculation. When the brightness and contrast values were calculated, those values were used to decided Gamma value and to correct the entire image. The brightness correction and fog removal were processed in parallel, and the images were registered as a single image to minimize the calculation time needed for all the processes. Then the feature extraction method HOG was used to detect the vehicle in the corrected image. As a result, it took 0.064 seconds per frame to detect the vehicle using image correction as proposed herein, which showed a 7.5% improvement in detection rate compared to the existing vehicle detection method.