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Machine Vision Row Crop Detection Using Blob Analysis and the Hough Transform

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Pp. 327-336 in Automation Technology for Off-Road Equipment, Proceedings of the July 26-27, 2002 Conference (Chicago, Illinois, USA)  701P0502.(doi:10.13031/2013.10022)
Authors:   F. Rovira-Más, Q. Zhang, J. F. Reid and J. D. Will
Keywords:   Automatic Guidance, Hough Transform, Parameter Space, Blob Analysis, Machine Vision

One of the main stages in the automatic guidance of agricultural vehicles is the detection of crop rows. The purpose of this paper is to present a machine vision algorithm to find the rows in a soybean field. A video camera was mounted on a tractor in order to capture real images, and send them to a computer for processing. The vision algorithm was based on the Hough transform and blob analysis techniques, and its outputs were the equations of the lines representing the rows. Between one and five lines were generally found to determine the desired trajectory. The information provided by these lines was effective to identify the path to be followed by the tractor. The algorithm overcame image noise problems.

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