• Title/Summary/Keyword: Epipolar Lines

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Development of the Advanced SURF Algorithm for Efficient Matching of Stereo Image (스테레오 영상의 효율적 매칭을 위한 개선된 SURF 알고리즘 개발)

  • Youm, Min Kyo;Yoon, Hong Sik;Whang, Jin Sang;Lee, Dong Ha
    • Journal of Korean Society for Geospatial Information Science
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    • v.21 no.2
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    • pp.11-17
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    • 2013
  • Nowadays 3D models are used in diverse sectors. The 3D maps provide better reality than existing plane maps as well as diverse pieces of information that cannot be expected from the limited plane maps. A process proposed in this paper enables easy and quick production by replacing the expensive laser scanners for modeling by an improved digital camera stereo matching algorithm. The algorithm used in this study was a SURF algorithm contained in the OpenCV library. The unconformity points of the algorithm were eliminated using the homography conversion and epipolar lines. In addition, the improved algorithm was compared with the commercial program, and it showed a better performance than the commercial program. It is expected that the proposed method can contribute to the digital maps and 3D virtual reality because it enables easy and quick 3D modeling provided that the stereo matching conditions are met.

Development of an Image Processing Algorithm for Paprika Recognition and Coordinate Information Acquisition using Stereo Vision (스테레오 영상을 이용한 파프리카 인식 및 좌표 정보 획득 영상처리 알고리즘 개발)

  • Hwa, Ji-Ho;Song, Eui-Han;Lee, Min-Young;Lee, Bong-Ki;Lee, Dae-Weon
    • Journal of Bio-Environment Control
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    • v.24 no.3
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    • pp.210-216
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    • 2015
  • Purpose of this study was a development of an image processing algorithm to recognize paprika and acquire it's 3D coordinates from stereo images to precisely control an end-effector of a paprika auto harvester. First, H and S threshold was set using HSI histogram analyze for extracting ROI(region of interest) from raw paprika cultivation images. Next, fundamental matrix of a stereo camera system was calculated to process matching between extracted ROI of corresponding images. Epipolar lines were acquired using F matrix, and $11{\times}11$ mask was used to compare pixels on the line. Distance between extracted corresponding points were calibrated using 3D coordinates of a calibration board. Non linear regression analyze was used to prove relation between each pixel disparity of corresponding points and depth(Z). Finally, the program could calculate horizontal(X), vertical(Y) directional coordinates using stereo camera's geometry. Horizontal directional coordinate's average error was 5.3mm, vertical was 18.8mm, depth was 5.4mm. Most of the error was occurred at 400~450mm of depth and distorted regions of image.