Research on Algorithm of Sugarcane Nodes Identification Based on Machine Vision

Abstract

In order to realize automatic cutting of sugarcane seeds in single bud segment, machine vision technology was used to identify sugarcane nodes. Firstly, the sugarcane color image was obtained, and the R component image of RGB color space was separated, and the median value of R component image was filtered and denoised. Second, the contour information of sugarcane image was obtained by FindContours function, and the area of interest of sugarcane image was selected by the width and height of contour. Finally, Sobel edge detection image of region of interest was acquired, and a rectangular detection operator was constructed to perform integral operation on the interested region to obtain a feature description vector of the interested region. Threshold value of the feature description vector was processed. The peak of the feature description vector was defined as the node feature point. The experimental results show that the recognition rate is 93% and the average time is 0.539 seconds.