• Title/Summary/Keyword: Crop row detection

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Crop-row Detection by Color Line Sensor

  • Ha, S.ta;T.Kobaysahi;K.Sakai
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1993.10a
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    • pp.353-362
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    • 1993
  • The purpose of this study is to develop a crop-row detector which can be applied to an automatic row following control for cultivators or thinning machines. In this report, a possibility of new crop-row detecting method was discussed. This detecting method consists of two principal means. One is the hardware means to convert the two dimensional crop-row vision to the compacted one dimensional information. The conversion is achieved by a color line sensor and a rotating mirror. In order to extract crop-row , R and G signals of RGB color system are used. The locations of two different points on the target row are detected by this means. Another is the software means to estimate the offset value and the heading angle between the detector and the target row which can be assumed as a straight line. As a result of discussion, it was concluded that this detecting method would be accurate enough for practical use.

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Guidance Line Extraction Algorithm using Central Region Data of Crop for Vision Camera based Autonomous Robot in Paddy Field (비전 카메라 기반의 무논환경 자율주행 로봇을 위한 중심영역 추출 정보를 이용한 주행기준선 추출 알고리즘)

  • Choi, Keun Ha;Han, Sang Kwon;Park, Kwang-Ho;Kim, Kyung-Soo;Kim, Soohyun
    • The Journal of Korea Robotics Society
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    • v.11 no.1
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    • pp.1-8
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    • 2016
  • 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.