• Title/Summary/Keyword: fish-eye image

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A Distortion Correction Method for the Fish-Eye Lens using Photogrammetric Techniques (사진측량 기법을 사용한 어안렌즈 왜곡보정에 관한 연구)

  • Kang, Jin-A;Park, Jae-Min;Kim, Byung-Guk
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2007.04a
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    • pp.161-164
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    • 2007
  • The paper studies in the wide-angle lens and distortion tendency and employs the correction techniques suitable to the fish-eye lens using the existing photographic survey methods. After carrying out the calibration of the the fish-eye lens, we calculated the correction parameters, and then developed the method that convert the original image-point to new image-point correcting distortion. The objectives of suggested calibration method in this paper are to calibrate the image of the the fish-eye lens used in the computer-vision and the control-instrumentation field widely. The proposed technique expects to improve the accuracy of the image of the fish-eye lens in the indoor tracking and monitoring field. Also the referenced cross point auto-extraction program is embodied for improving efficiency of the lens correction techniques. Consequently, this calibration method would be applied to the automated distorting correction method on not only the fish-eye lens also general lens.

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An Observation System of Hemisphere Space with Fish eye Image and Head Motion Detector

  • Sudo, Yoshie;Hashimoto, Hiroshi;Ishii, Chiharu
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.663-668
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    • 2003
  • This paper presents a new observation system which is useful to observe the scene of the remote controlled robot vision. This system is composed of a motionless camera and head motion detector with a motion sensor. The motionless camera has a fish eye lens and is for observing a hemisphere space. The head motion detector has a motion sensor is for defining an arbitrary subspace of the hemisphere space from fish eye lens. Thus processing the angular information from the motion sensor appropriately, the direction of face is estimated. However, since the fisheye image is distorted, it is unclear image. The partial domain of a fish eye image is selected by head motion, and this is converted to perspective image. However, since this conversion enlarges the original image spatially and is based on discrete data, crevice is generated in the converted image. To solve this problem, interpolation based on an intensity of the image is performed for the crevice in the converted image (space problem). This paper provides the experimental results of the proposed observation system with the head motion detector and perspective image conversion using the proposed conversion and interpolation methods, and the adequacy and improving point of the proposed techniques are discussed.

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A Study on the Design of Fish-Eye Optic for Automotive Stop Light (자동차용 제동등을 위한 FISH-EYE OPTIC 설계에 관한 연구)

  • 임지만;이정환;서명원
    • Transactions of the Korean Society of Automotive Engineers
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    • v.7 no.6
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    • pp.231-240
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    • 1999
  • The most important thing to be considered in designing stop lamps for automobiles is to satisfy the photometric requirement in various countries and achieve the equal image. To meet these requirements, parabolic reflector and fish-eye optics has been widely applied. The form of the embodied optic is most important in satisfying the photometric requirement and achieving the equal image because the impact of fish-eye optic is decisive. In this study, a series of researches has been performed to optimize of the fish-eye optic by analyzing beam pattern through the photometric simulation based on CATAI program. The optimized results have been shown to meet the various photometric requirements including non dazzling condition considering the following car. The methodology of this study is excepted to influence the development procedure of light system. The time and cost for the system development would be greatly saved by suing this simulaion technique.

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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.

Neural network based distortion correction of wide angle lens (신경회로망을 이용한 광각렌즈의 왜곡보정)

  • 정규원
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.299-301
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    • 1996
  • Since a standard lens has small sight angle, a fish-eye lens can be used in order to obtain wide sight angle for the robot vision system. In spite of the advantage, the image through the lens has variable resolution; the central information of the lens is of high resolution, but the peripheral information is of low resolution. Owing to this difference of resolution, the variable resolution image should be transformed to a uniform resolution image in order to determine the positions of the objects in the image. In this work, the correction method for the distorted image is presented and the performance is analyzed. Furthermore, the camera with a fish eye lens can be used to determine the real world coordinates. The performance is shown through experiments.

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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.

Geometric Correction of Vehicle Fish-eye Lens Images (차량용 어안렌즈영상의 기하학적 왜곡 보정)

  • Kim, Sung-Hee;Cho, Young-Ju;Son, Jin-Woo;Lee, Joong-Ryoul;Kim, Myoung-Hee
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.601-605
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    • 2009
  • Due to the fact that fish-eye 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. Camera calibration should be preceded, and geometrical correction on the radial distortion is needed to provide the images for the driver's assistance. However, vehicle fish-eye cameras have diagonal output images rather than circular images and have asymmetric distortion beyond the horizontal angle. In this paper, we introduce a camera model and metric calibration method for vehicle cameras which uses feature points of the image. And undistort the input image through a perspective projection, where straight lines should appear straight. The method fitted vehicle fish-eye lens with different field of views.

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Camera Calibration and Barrel Undistortion for Fisheye Lens (차량용 어안렌즈 카메라 캘리브레이션 및 왜곡 보정)

  • Heo, Joon-Young;Lee, Dong-Wook
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.62 no.9
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    • pp.1270-1275
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    • 2013
  • A lot of research about camera calibration and lens distortion for wide-angle lens has been made. Especially, calibration for fish-eye lens which has 180 degree FOV(field of view) or above is more tricky, so existing research employed a huge calibration pattern or even 3D pattern. And it is important that calibration parameters (such as distortion coefficients) are suitably initialized to get accurate calibration results. It can be achieved by using manufacturer information or lease-square method for relatively narrow FOV(135, 150 degree) lens. In this paper, without any previous manufacturer information, camera calibration and barrel undistortion for fish-eye lens with over 180 degree FOV are achieved by only using one calibration pattern image. We applied QR decomposition for initialization and Regularization for optimization. With the result of experiment, we verified that our algorithm can achieve camera calibration and image undistortion successfully.

Omni-directional Vision SLAM using a Motion Estimation Method based on Fisheye Image (어안 이미지 기반의 움직임 추정 기법을 이용한 전방향 영상 SLAM)

  • Choi, Yun Won;Choi, Jeong Won;Dai, Yanyan;Lee, Suk Gyu
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.8
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    • pp.868-874
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    • 2014
  • This paper proposes a novel mapping algorithm in Omni-directional Vision SLAM based on an obstacle's feature extraction using Lucas-Kanade Optical Flow motion detection and images obtained through fish-eye lenses mounted on robots. Omni-directional image sensors have distortion problems because they use a fish-eye lens or mirror, but it is possible in real time image processing for mobile robots because it measured all information around the robot at one time. In previous Omni-Directional Vision SLAM research, feature points in corrected fisheye images were used but the proposed algorithm corrected only the feature point of the obstacle. We obtained faster processing than previous systems through this process. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we remove the feature points of the floor surface using a histogram filter, and label the candidates of the obstacle extracted. Third, we estimate the location of obstacles based on motion vectors using LKOF. Finally, it estimates the robot position using an Extended Kalman Filter based on the obstacle position obtained by LKOF and creates a map. We will confirm the reliability of the mapping algorithm using motion estimation based on fisheye images through the comparison between maps obtained using the proposed algorithm and real maps.

Localization using Ego Motion based on Fisheye Warping Image (어안 워핑 이미지 기반의 Ego motion을 이용한 위치 인식 알고리즘)

  • Choi, Yun Won;Choi, Kyung Sik;Choi, Jeong Won;Lee, Suk Gyu
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.1
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    • pp.70-77
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    • 2014
  • This paper proposes a novel localization algorithm based on ego-motion which used Lucas-Kanade Optical Flow and warping image obtained through fish-eye lenses mounted on the robots. The omnidirectional image sensor is a desirable sensor for real-time view-based recognition of a robot because the all information around the robot can be obtained simultaneously. The preprocessing (distortion correction, image merge, etc.) of the omnidirectional image which obtained by camera using reflect in mirror or by connection of multiple camera images is essential because it is difficult to obtain information from the original image. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we extract motion vectors using Lucas-Kanade Optical Flow in preprocessed image. Third, we estimate the robot position and angle using ego-motion method which used direction of vector and vanishing point obtained by RANSAC. We confirmed the reliability of localization algorithm using ego-motion based on fisheye warping image through comparison between results (position and angle) of the experiment obtained using the proposed algorithm and results of the experiment measured from Global Vision Localization System.