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비전 카메라 기반의 무논환경 자율주행 로봇을 위한 중심영역 추출 정보를 이용한 주행기준선 추출 알고리즘

Guidance Line Extraction Algorithm using Central Region Data of Crop for Vision Camera based Autonomous Robot in Paddy Field

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초록

In this paper, we propose a new algorithm of the guidance line extraction for autonomous agricultural robot based on vision camera in paddy field. It is the important process for guidance line extraction which finds the central point or area of rice row. We are trying to use the central region data of crop that the direction of rice leaves have convergence to central area of rice row in order to improve accuracy of the guidance line. The guidance line is extracted from the intersection points of extended virtual lines using the modified robust regression. The extended virtual lines are represented as the extended line from each segmented straight line created on the edges of the rice plants in the image using the Hough transform. We also have verified an accuracy of the proposed algorithm by experiments in the real wet paddy.

Abstract

In this paper, we propose a new algorithm of the guidance line extraction for autonomous agricultural robot based on vision camera in paddy field. It is the important process for guidance line extraction which finds the central point or area of rice row. We are trying to use the central region data of crop that the direction of rice leaves have convergence to central area of rice row in order to improve accuracy of the guidance line. The guidance line is extracted from the intersection points of extended virtual lines using the modified robust regression. The extended virtual lines are represented as the extended line from each segmented straight line created on the edges of the rice plants in the image using the Hough transform. We also have verified an accuracy of the proposed algorithm by experiments in the real wet paddy.

참고문헌 (10)

  1. Keun Ha Choi, "Vision camera based autonomous guidance algorithm using extraction data of central region for precision weeding robot", The 10 Korea Robotics Society Annual Conference, pp.1~4 (2015)
  2. 최근하, "논 잡초 방제용 자율주행 로봇을 위한 벼의 형태학적 특징 기반의 주행기준선 추출", 로봇학회 논문지, 9(3), pp.147~153 (2014), 한국로봇학회
  3. H.T. Søgaard, "Determination of crop rows by image analysis without segmentation", Computers and Electronics in Agriculture, 38, pp.141~158 (2003)
  4. S. Hana, "A guidance directrix approach to vision-based vehicle guidance systems", Computers and Electronics in Agriculture, 43, pp.179~195 (2004)
  5. F. Rovira-Ma´s, "Hough-transform-based vision algorithm for crop row detection of an automated agricultural vehicle", Proc. IMechE, 219, pp.999~1010 (2005)
  6. Tijmen Bakkera, "A vision based row detection system for sugar beet", Computers and Electronics in Agriculture, 60, pp.87~95 (2008)
  7. Ronghua Ji, "Crop-row detection algorithm based on Random Hough Transformation", Mathematical and Computer Modelling, 54, pp.1016~1020 (2011)
  8. J. Billingsley, "The successful development of a vision guidance system for agriculture", Computers and Electroncis in Agriculture, 16, pp.147~163 (1997)
  9. J. Romeo, "Crop row detection in maize fields inspired on the human visual perception", The Scientific World Journal, pp.1~10 (2012)
  10. Keun Ha Choi, "Morphologybased guidance line extraction for an autonomous weeding robot in paddy fields", Computers and Electronics in Agriculture, 113, pp.266~274 (2015)

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