Detection of Maize Navigation Centerline Based on Machine Vision

For the problem of automatic mechanical navigation in maize fields, we studied the maize navigation centerline by collecting maize root images. In this paper, through the RGB color model, the red feature is used to extract the roots of the maize plants. Next, according to the shape characteristics of the root target, the minimum bounding rectangle is used to determine the positioning character points of maize roots. Then, the least square method is used to fit these positioning points which are obtained by calculation in order to extract the root row lines. Finally, by calculating the slopes of the root row lines, we are able to get the actual navigation centerline. The experiment showed the result that compared with other algorithms, the algorithm of this paper takes less time to extract the navigation centerline. In other different environments, the accuracy of the navigation centerline extracted by this algorithm is above 92%. Therefore, this algorithm has strong robustness and real-time performance. This paper provides a reliable navigation method for the autonomous walking of agricultural machinery in maize fields. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.