• 제목/요약/키워드: fish-eye image

검색결과 34건 처리시간 0.023초

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

  • 강진아;박재민;김병국
    • 한국측량학회:학술대회논문집
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    • 한국측량학회 2007년도 춘계학술발표회 논문집
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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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    • 제어로봇시스템학회 2003년도 ICCAS
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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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자동차용 제동등을 위한 FISH-EYE OPTIC 설계에 관한 연구 (A Study on the Design of Fish-Eye Optic for Automotive Stop Light)

  • 임지만;이정환;서명원
    • 한국자동차공학회논문집
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    • 제7권6호
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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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어안 렌즈를 이용한 전방향 감시 및 움직임 검출 (Omni-directional Surveillance and Motion Detection using a Fish-Eye Lens)

  • 조석빈;이운근;백광렬
    • 대한전자공학회논문지SP
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    • 제42권5호
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    • pp.79-84
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    • 2005
  • 일반적인 카메라의 시야는 사람에 비하여 매우 좁기 때문에 큰 물체를 한 화면으로 얻기 힘들며, 그 움직임도 넓게 감시하기에 어려움 점이 많다. 이에 본 논문에서는 어안 렌즈(Fish-Eye Lens)를 사용하여 넓은 시야의 영상을 획득하고 전방향 감시를 위한 투시(perspective) 영상과 파노라마(panorama) 영상을 복원하는 방법을 제시한다. 영상 변환 과정에서 어안 렌즈의 특성으로 인한 해상도 차이를 보완하기 위하여 여러 가지 영상 보간법을 적용하고 결과를 비교하였다. 그리고 ME(Moving Edge) 방법으로 움직임을 검출하여 다중 물체를 추적할 수 있도록 하였다.

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

  • 정규원
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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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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시설물 감시용 CCTV의 초광각 렌즈 왜곡보정 (The Fish-eye Lens Distortion Correction of Facilities Monitoring CCTV)

  • 강진아;남상관;김태훈;오윤석
    • 한국측량학회지
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    • 제27권3호
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    • pp.323-330
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    • 2009
  • 최근 도시시설물의 안전과 범죄 모니터링에 대한수요가 증가하고 있으나, 사용되는 산업장비용 CCTV의 경우 고가가 대부분이다. 본 연구에서는 초 광각 렌즈인 어안렌즈와 사진측량 알고리즘을 이용하여 단일 카메라의 시야각을 증대시켜 모니터링의 효율성을 극대화 시키고자 한다. 어안렌즈를 이용한 모니터링을 위해 우선 실험실 내에서 왜곡계수 산출 실험을 실시하였는데 이는 일정 간격의 고정된 종이 타겟을 여러 방향에서 촬영한 후, 격자점을 이용하여 왜곡 계수를 추출하였다. 또한 추출된 왜곡보정 계수를 보정 및 모니터링 프로그램에 삽입하여 실시간 보정된 영상을 획득할 수 있다. 또한 보정된 영상에 대한 검증을 위해, 타겟을 스캐닝하여 왜곡 보정된 영상과 비교한 결과 RMSE가 3.2pixel로 나타났다.

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

  • 김성희;조영주;손진우;이중렬;김명희
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2009년도 학술대회
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    • pp.601-605
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    • 2009
  • $180^{\circ}$ 이상의 영역을 획득하는 어안렌즈(fish-eye lens)는 최소의 카메라로 최대 시야각을 확보할 수 있는 장점으로 인해 차량 장착 시도가 늘고 있다. 운전자에게 현실감 있는 영상을 제공하고 센서로 이용하기 위해서는 캘리브레이션을 통해 방사왜곡(radial distortion)에 따른 기하학적인 왜곡 보정이 필요하다. 그런데 차량용 어안렌즈의 경우, 대각선 어안렌즈로 일반 원상 어안렌즈로 촬영한 둥근 화상의 바깥둘레에 내접하는 부분을 잘라낸 직사각형 영상과 같으며, 수직, 수평 화각에 따라 왜곡이 비대칭구조로 설계되었다. 본 논문에서는, 영상의 특징점(feature points)을 이용하여 차량용 어안렌즈에 적합한 카메라 모델 및 캘리브레이션 기법을 소개한다. 캘리브레이션한 결과, 제안한 방법은 화각이 다른 차량용 어안렌즈에도 적용 가능하다.

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

  • 허준영;이동욱
    • 전기학회논문지
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    • 제62권9호
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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.

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

  • 최윤원;최정원;대염염;이석규
    • 제어로봇시스템학회논문지
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    • 제20권8호
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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.

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

  • 최윤원;최경식;최정원;이석규
    • 제어로봇시스템학회논문지
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    • 제20권1호
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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.