Extraction of navigation line based on improved grayscale factor in corn field

Abstract

ABSTRACT: Focusing on the problem that corn plant in different growth periods is grayed out by known methods, the gray scale difference of different part is large or the soil discrimination degree is not high, the navigation path is low in accuracy and speed. This paper proposed a new method for extracting cornfield navigation baselines, which is used to control walking of agricultural robots. Design method included image segmentation, navigation point extraction, and navigation path fitting. Image segmentation is based on a new grayscale factor combined with median filtering, OSTU method and morphological operations to achieve the separation of crops and soil. The extraction of the navigation point is based on the binary image vertical projection map to obtain the region of interest, and the navigation point coordinates are determined by calculating the relative center point of the white pixel points of the sampling line in the region of interest. The Hough transform is used to fit the navigation point obtained by the vertical projection map to determine the navigation path, and then the control parameters are obtained. The gray scale factor that is improved in this paper combined with the vertical projection map can extract the target ridge with an accuracy rate of 92%, and the accuracy of extracting the navigation line is more than 90%. When conducting navigation tracking experiments in corn field, the maximum error is 5cm.