• Title/Summary/Keyword: 자동왜곡보정프로그램

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Automatic Detection Method of Corners of Grid Patterns from Distortion Corrected Image (왜곡보정 영상에서의 그리드 패턴 코너의 자동 검출 방법)

  • Cheon, Sweung-hwan;Jang, Si-Woong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.499-503
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    • 2013
  • 자동차를 위한 전방향(omni-directional) 감시 시스템, 로봇의 시각 역할 등 다양한 비전 시스템에서 카메라가 장착되어 사용되고 있다. AVM(Around View Monitoring) 시스템에서 그리드 패턴의 코너를 검출하기 위해서는 먼저, 광각 카메라에서 획득한 비선형적인 방사 왜곡을 가진 영상의 왜곡 보정 작업을 수행하여야 한다. 이후에 왜곡이 보정된 영상 내부의 그리드 패턴 각 코너들을 자동으로 검출하기 위해서 Sub-Pixel, 허프 변환 등의 여러 가지 방법이 있으며 현재 출시된 AVM 시스템에 직선이나 교점 및 코너 검출을 위해 사용되고 있다. 본 논문에서는 왜곡 보정 영상을 입력 영상으로 받아 그리드 패턴의 코너를 자동으로 검출하는 프로그램을 설계한다. 제안하는 코너 검출 방법을 직접 구현하여 성능을 평가함으로써 AVM 시스템에서 코너를 검출하는 부분에 적용시킬 수 있음을 보인다.

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The Research for the Wide-Angle Lens Distortion Correction by Photogrammetry Techniques (사진측량 기법을 사용한 광각렌즈 왜곡보정에 관한 연구)

  • Kang, Jin-A;Park, Jae-Min;Kim, Byung-Guk
    • 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.

Assessment of Imaging Distortion in Magnetic Resonance Imaging for Stereotactic Radiosurgery: Through Phantom Study (뇌정위 방사선수술 시스템을 위한 자기공명영상의 공간적 왜곡의 측정 : 모형실험을 통한 연구)

  • 박선원;한문희;김동규;정현태;송인찬
    • Investigative Magnetic Resonance Imaging
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    • v.4 no.1
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    • pp.7-13
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    • 2000
  • Purpose : To assess the distortion of MRI with the Leksell stereotactic radiosurgery system in variable pulse sequence and imaging plane through phantom study, to find most adequate imaging plane and pulse sequence for stereotactic radiosurgery system. Materials and methods : We made the phantoms for MRI and get images in variable conditions and analyzed the image distortion using image analysis program, and statistically using paired student t-test. Results : The transeverse plane images had acceptable error ranges bless than 1.5mm) in all pulse sequence in both the analysis of fiducial marker in stereotactic G-frame and the phantom study. The coronal plane images had unacceptable large errors (more than 1.7mm) in the analysis of fiducial marker in the stereotactic G-frame, but had corrected small errors (less than 1.5mm) in the phantom study. Conclusion : We find from the phantom study that the present MR machines are adequate for stereotactic surgery system in frequently used pulse sequences, and imaging planes.

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Genetic Algorithm Calibration Method and PnP Platform for Multimodal Sensor Systems (멀티모달 센서 시스템용 유전자 알고리즘 보정기 및 PnP 플랫폼)

  • Lee, Jea Hack;Kim, Byung-Soo;Park, Hyun-Moon;Kim, Dong-Sun;Kwon, Jin-San
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.1
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    • pp.69-80
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    • 2019
  • This paper proposes a multimodal sensor platform which supports plug and play (PnP) technology. PnP technology automatically recognizes a connected sensor module and an application program easily controls a sensor. To verify a multimodal platform for PnP technology, we build up a firmware and have the experiment on a sensor system. When a sensor module is connected to the platform, a firmware recognizes the sensor module and reads sensor data. As a result, it provides PnP technology to simply plug sensors without any software configuration. Measured sensor raw data suffer from various distortions such as gain, offset, and non-linearity errors. Therefore, we introduce a polynomial calculation to compensate for sensor distortions. To find the optimal coefficients for sensor calibration, we apply a genetic algorithm which reduces the calibration time. It achieves reasonable performance using only a few data points with reducing 97% error in the worst case. The platform supports various protocols for multimodal sensors, i.e., UART, I2C, I2S, SPI, and GPIO.

ALGORITHMS FOR MOVING OBJECT DETECTION: YSTAR-NEOPAT SURVEY PROGRAM (이동천체 후보 검출을 위한 알고리즘 개발: YSTAR-NEOPAT 탐사프로그램)

  • Bae, Young-Ho;Byun, Yong-Ik;Kang, Yong-Woo;Park, Sun-Youp;Oh, Se-Heon;Yu, Seoung-Yeol;Han, Won-Young;Yim, Hong-Suh;Moon, Hong-Kyu
    • Journal of Astronomy and Space Sciences
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    • v.22 no.4
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    • pp.393-408
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    • 2005
  • We developed and compared two automatic algorithms for moving object detections in the YSTAR-NEOPAT sky survey program. One method, called starlist comparison method, is to identify moving object candidates by comparing the photometry data tables from successive images. Another method, called image subtraction method, is to identify the candidates by subtracting one image from another which isolates sources moving against background stars. The efficiency and accuracy of these algorithms have been tested using actual survey data from the YSTAR-NEOPAT telescope system. For the detected candidates, we performed eyeball inspection of animated images to confirm validity of asteroid detections. Main conclusions include followings. First, the optical distortion in the YSTAR-NEOPAT wide-field images can be properly corrected by comparison with USNO-B1.0 catalog and the astrometric accuracy can be preserved at around 1.5 arcsec. Secondly, image subtraction provides more robust and accurate detection of moving objects. For two different thresholds of 2.0 and $4.0\sigma$, image subtraction method uncovered 34 and 12 candidates and most of them are confirmed to be real. Starlist comparison method detected many more candidates, 60 and 6 for each threshold level, but nearly half of them turned out to be false detections.