A new design of sugarcane seed cutting systems based on machine vision
Deqiang Zhou, Yunlei Fan, Ganran Deng, Fengguang He, Meili Wang
Abstract
In order to realize anti-damage bud and automatic cutting of sugarcane in a single bud segment, a sugarcane cutting system based on machine vision is designed. The seed cutting system includes a mechanical part, electrical part, and visual processing part. The core of the system uses machine vision to identify the segments of sugarcane stalks. The feasibility of the system and the identification effect can be better verified based on designing a prototype for seed cutting. The results of the off-line identification of sugarcane stalk segments show that the recognition rate is 93% and the average time is 0.539 s. The throughput capacity of the developed system with single cutting unit can range up to 2400 buds/h. The on-line test illustrated that the position precision of cutting point can meet the demand of agriculture, and the rate of bud damage is zero.