Affiliation:
1. Shanghai Vocational College of Agriculture and Forestry, Shanghai/China
2. Robotics and Microsystems Centre, Soochow University, Suzhou/China
Abstract
In the scene of paddy field rotary tillage, a real-time detection method of rotary tillage condition based on machine vision is proposed, and the quality of rotary tillage is evaluated by the index of residual stubble. The residual root stubble is selected as the research object, and the root stubble detection method based on the standard deviation of Y component in YCrCb space is proposed to determine the residual root stubble of soil after rotary tillage, which is divided into three levels: less root stubble, medium root stubble, and more root stubble. Finally, the accuracy of the algorithm is verified by field test and questionnaire survey. On the basis of manual evaluation, the accuracy rate of the working condition is 83.6 %, which provides a more accurate basis for the real-time adjustment of the control strategy for the unmanned operation of agricultural machinery in the field, and realizes the rotary tillage quality from qualitative evaluation to quantitative evaluation, and lays the foundation for the data of rotary tillage quality.
Subject
Industrial and Manufacturing Engineering,Mechanical Engineering,Food Science