• Title/Summary/Keyword: 어안

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A Study on Fisheye Lens based Features on the Ceiling for Self-Localization (실내 환경에서 자기위치 인식을 위한 어안렌즈 기반의 천장의 특징점 모델 연구)

  • Choi, Chul-Hee;Choi, Byung-Jae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.4
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    • pp.442-448
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    • 2011
  • There are many research results about a self-localization technique of mobile robot. In this paper we present a self-localization technique based on the features of ceiling vision using a fisheye lens. The features obtained by SIFT(Scale Invariant Feature Transform) can be used to be matched between the previous image and the current image and then its optimal function is derived. The fisheye lens causes some distortion on its images naturally. So it must be calibrated by some algorithm. We here propose some methods for calibration of distorted images and design of a geometric fitness model. The proposed method is applied to laboratory and aile environment. We show its feasibility at some indoor environment.

The Fish-eye Lens Distortion Correction of Facilities Monitoring CCTV (시설물 감시용 CCTV의 초광각 렌즈 왜곡보정)

  • Kang, Jin-A;Nam, Sang-Kwan;Kim, Tae-Hoon;Oh, Yoon-Seok
    • 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.

Tunnel Mosaic Images Using Fisheye Lens Camera (어안렌즈 카메라를 이용한 터널 모자이크 영상 제작)

  • Kim, Gi-Hong;Song, Yeong-Sun;Kim, Baek-Seok
    • Journal of Korean Society for Geospatial Information Science
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    • v.17 no.1
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    • pp.105-111
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    • 2009
  • A construction can be more convenient and safer with adequate informations. Consequently, studies on collecting various informations using newest surveying technology and applying these informations to a construction have been making progress recently. Digital images are easy to obtain and contain various informations. Therefore, with the recent development of image processing technology, the application field of digital images is getting wider. In this study, we proposed to use a fisheye lens camera in underground construction sites, especially tunnels, to overcome inconvenience in photographing with general lens cameras. A program for mapping the surface of a tunnel and making a mosaic image is also developed. This mosaic image can be applied to observe and analyze abnormal phenomenons on tunnel surface like cracks, water leakage, exfoliates, and so on.

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Omni-directional Surveillance and Motion Detection using a Fish-Eye Lens (어안 렌즈를 이용한 전방향 감시 및 움직임 검출)

  • Cho, Seog-Bin;Yi, Un-Kun;Baek, Kwang-Ryul
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.5 s.305
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    • pp.79-84
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    • 2005
  • In this paper, we developed an omni-directional surveillance and motion detection method. The fish-eye lens provides a wide field of view image. Using this image, the equi-distance model for the fish-eye lens is applied to get the perspective and panorama images. Generally, we must consider the trade-off between resolution and field of view of an image from a camera. To enhance the resolution of the result images, some kind of interpolation methods are applied. Also the moving edge method is used to detect moving objects for the object tracking.

Image Data Loss Minimized Geometric Correction for Asymmetric Distortion Fish-eye Lens (비대칭 왜곡 어안렌즈를 위한 영상 손실 최소화 왜곡 보정 기법)

  • Cho, Young-Ju;Kim, Sung-Hee;Park, Ji-Young;Son, Jin-Woo;Lee, Joong-Ryoul;Kim, Myoung-Hee
    • Journal of the Korea Society for Simulation
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    • v.19 no.1
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    • pp.23-31
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    • 2010
  • Due to the fact that fisheye lens can provide super wide angles with the minimum number of cameras, field-of-view over 180 degrees, many vehicles are attempting to mount the camera system. Not only use the camera as a viewing system, but also as a camera sensor, camera calibration should be preceded, and geometrical correction on the radial distortion is needed to provide the images for the driver's assistance. In this thesis, we introduce a geometric correction technique to minimize the loss of the image data from a vehicle fish-eye lens having a field of view over $180^{\circ}$, and a asymmetric distortion. Geometric correction is a process in which a camera model with a distortion model is established, and then a corrected view is generated after camera parameters are calculated through a calibration process. First, the FOV model to imitate a asymmetric distortion configuration is used as the distortion model. Then, we need to unify the axis ratio because a horizontal view of the vehicle fish-eye lens is asymmetrically wide for the driver, and estimate the parameters by applying a non-linear optimization algorithm. Finally, we create a corrected view by a backward mapping, and provide a function to optimize the ratio for the horizontal and vertical axes. This minimizes image data loss and improves the visual perception when the input image is undistorted through a perspective projection.

Correction of Fisheye Distortion and Perspective Distortion (어안렌즈왜곡 및 원근왜곡의 보정)

  • Song, Gwang-Yul;Yoon, Pal-Joo;Lee, Joon-Woong
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.10
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    • pp.22-29
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    • 2006
  • This paper considers the lens distortions such as a fisheye distortion and a perspective distortion. While a fisheye lens has a wide field-of-view, it causes a large distortion to the images. Regardless of a fisheye lens or a rectilinear lens, a lens generates perspective distortion in a vertical direction when the lens views in an upward direction or downward direction. These distortions deform images differently from human visual functions. Therefore, this paper presents a method to correct the distortions, and whereby, the research in this paper enlarges choices of images to image processing algorithm that may select the distorted images and the corrected images depending on applications. An infinite polynomial model is employed in the fisheye radial distortion correction, and the vertical perspective distortion correction is done by using a vanishing point. The methods introduced in this paper are implemented on the images captured by a rear-view camera installed on a vehicle and showed their robustness of the correction.

An Interpolation Method for a Barrel Distortion Using Nearest Pixels on a Corrected Image (방사왜곡을 고려한 보정 영상 위최근접 화소 이용 보간법)

  • Choi, Changwon;Yi, Joonhwan
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.7
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    • pp.181-190
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    • 2013
  • We propose an interpolation method considering barrel distortion of fisheye lens using nearest pixels on a corrected image. The correction of barrel distortion comprises coordinate transformation and interpolation. This paper focuses on interpolation. The proposed interpolation method uses nearest four coordinates on a corrected image rather than on a distorted image unlike existing techniques. Experimental results show that both subjective and objective image qualities are improved.

FisheyeNet: Fisheye Image Distortion Correction through Deep Learning (FisheyeNet: 딥러닝을 활용한 어안렌즈 왜곡 보정)

  • Lee, Hongjae;Won, Jaeseong;Lee, Daeun;Rhee, Seongbae;Kim, Kyuheon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2021.06a
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    • pp.271-274
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    • 2021
  • Fisheye 카메라로 촬영된 영상은 일반 영상보다 넓은 시야각을 갖는 장점으로 여러 분야에서 활용되고 있다. 그러나 fisheye 카메라로 촬영된 영상은 어안렌즈의 곡률로 인하여 영상의 중앙 부분은 팽창되고 외곽 부분은 축소되는 방사 왜곡이 발생하기 때문에 영상을 활용함에 있어서 어려움이 있다. 이러한 방사 왜곡을 보정하기 위하여 기존 영상처리 분야에서는 렌즈의 곡률을 수학적으로 계산하여 보정하기도 하지만 이는 각각의 렌즈마다 왜곡 파라미터를 추정해야 하기 때문에, 개별적인 GT (Ground Truth) 영상이 필요하다는 제한 사항이 있다. 이에 본 논문에서는 렌즈의 종류마다 GT 영상을 필요로 하는 기존 기술의 제한 사항을 극복하기 위하여, fisheye 영상만을 입력으로 하여 왜곡계수를 계산하는 딥러닝 네트워크를 제안하고자 한다. 또한, 단일 왜곡계수를 왜곡모델로 활용함으로써 layer 수를 크게 줄일 수 있는 경량화 네트워크를 제안한다.

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Camera Module for Vehicle Safety (차량 안전용 카메라 모듈)

  • Shin, Seong-Yoon;Cho, Seung-Pyo;Lee, Hyun-Chang;Shin, Kwang-Seong
    • 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.

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