Hough-transform-based vision algorithm for crop row detection of an automated agricultural vehicle

Abstract

Finding a pathway between crop rows is essential for automated guidance of some agricultural vehicles. The research reported in this paper developed a vision-based method for detecting crop rows. This method applied the Hough transform and connectivity analysis to process images of a vehicle's forward view and to use them to find the appropriate pathway in the field. The Hough transform was used to detect crop rows and the connectivity analysis was applied to identify the most suitable path from all possible choices. This system was implemented in an agricultural tractor and tested in both laboratory and field experiments. The methodology devised overcame image noise problems and successfully determined the proper trajectory for the tractor.

Automatic expert system based on images for accuracy crop row detection in maize fields

“…Gee, Bossu, Jones, and Truchetet (2008) apply a double Hough transform under the assumption that crop rows are the only lines of the image converging to the vanishing point, the remainder lines are rejected, additional constraints such as inter-row spacing and perspective geometry concepts help to identify the lines. It is required to determine the threshold required by the Hough transform to determine maximum peaks values (Jones, Gée, & Truchetet, 2009a, 2009b or predominant peaks (Rovira-Más, Zhang, Reid, & Will, 2005). Depending on the crop densities several lines could be feasible and a posterior merging process is applied to lines with similar parameters Tellaeche et al, 2011).…”

“…A lot of lines, with different slopes, appear for a unique crop row. This requires a careful peak thresholding selection (Jones et al, 2009a(Jones et al, , 2009bRovira-Más et al, 2005).…”

Guidance Line Extraction for Autonomous Weeding robot based-on Rice Morphology Characteristic in Wet Paddy

“…다음으로 허프변환을 이용한 연구로서 Marchant [7] 는 인 식된 근적외선 이진영상에서 허프변환을 이용하여 주행기 준선을 추출하였다. Rovira-Más [8] 는 허프변환의 효율성을 높이기 위해 작물열 영상의 중앙점을 연결한 골격화 선을 허프변환에 적용하여 기준선을 획득하였고, Bakkera [9] 는 작 물열이 있는 공간을 사각 영역으로 분할한 후 각 영상을 하나로 융합하여 그레이 값의 밀도를 높인 후 허프변환을 실시하여 영상 처리시간을 단축하고자 했다. Ronghua Ji [10] 역시 Randomized-허프변환을 통해 계산시간 증가 문제를 해결하고자 했다.…”

Automated System for Targeted Spraying in Orchards by Using RGB Imaging

“…Positioning of spray nozzles was not controlled online. It is assumed that imaging algorithms can evolve in the future as already reported by Rovira-Más et al (2005) to such an extent that it would be possible to detect the shape of trees and to guide simultaneously, not only the flow rate, but also the position the spray nozzles.…”

“…Recently, the Hough-transformbased vision algorithm for crop row detection of an automated agricultural vehicle was reported to be the most promising method in orchard management (Kise et al 2005;Rovira-Más et al 2005).…”