• Title/Summary/Keyword: CGD camera

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Development of Displacement Measurement System of Structures Using Image Processing Techniques (영상처리기술을 이용한 구조물의 변위 측정 시스템의 개발)

  • 김성욱;김상봉;서진호
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.8
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    • pp.673-679
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    • 2004
  • In this paper, we develop the displacement measurement system of multiple moving objects based on image processing techniques. The image processing method adopts inertia moment theory for obtaining the centroid measurement of the targets and basic processing algorithm of gray, binary, closing, labeling and so on. To get precise displacement measurement in spite of multiple moving targets, a CGD camera with zoom is used and the position of camera is changed by a pan/tilt system. The fiducial marks on the fixed positions are used as the sensing points for the image processing to recognize the position errors in direction of XY-coordinates. The precise alignment device is pan/tilt of XY-type and the pan/tilt is controlled by DC servomotors which are driven by a microprocessor. Morover, the centers of fiducial marks are obtainted by an inertia moment method. By applying the developed precise position control system for multiple targets, the displacement of multiple moving targets are detected automatically and are also stored in the database system in a real time. By using database system and internet, the displacement datum can be confirmed at a great distance and analyzed. Finally, the effectiveness of developed system is shown in experimental results and realized the precision about 0.12[mm] in the position control of XY-coordinates.

Crack Detection and Sorting of Eggs by Image Processing (영상처리에 의한 계란의 파란 검출 및 선별)

  • Cho, H.K.;Kwon, Y.;Cho, S.K.
    • Korean Journal of Poultry Science
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    • v.22 no.4
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    • pp.233-238
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    • 1995
  • A computer vision system was built to generate images of a single, stationary egg. This system includes a CGD camera, a frame grabber, and incandescent back lighting system. Image processing algorithms were developed to inspect egg shell and to sort eggs. Those values of both gray level and area of dark spots in the egg image were used as criteria to detect holes in egg and those values of both area and roundness of dark spots in the egg image were used to detect cracks in egg. For a sample of 300 eggs, this system was able to correctly analyze an egg for the presence of a defect 97.5% of the time. The weights of eggs were found to be linear to both the projected area and the perimeter of eggs viewed from above. Those two values were used as criteria to sort eggs. The coefficients of determination(r$^2$) for the regression equations between weights and those two values were 0.967 and 0.972 in the two sets of experiment. Accuracies in grading were found to be 95.6% and 96.7% as compared with results from sizing by electronic weight scale.

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