Detection Method of Straw Mulching Unevenness with RGB-D Sensors

Abstract

Returning straw to the field is very important of for the conservation tillage to increase land fertility. It is vital to detect the unevenness of the straw covering to evaluate the performance of no-tillage planter, especially for the ones with returning full amount of straw. In this study, two kinds of RGB-D(Red, Green, Blue-Depth) sensors (RealSense D435i and Kinect v2) were applied to estimate the straw mulching unevenness by detecting the depth of straw coverage. Firstly, the overall structure and working principle of no-tillage planter with returning the full amount of straw was introduced. Secondly, field images were captured with the two kinds of RGB-D sensors after no tillage planter operation. Thirdly, straw covering unevenness computing was carried on a system developed by Matlab. Finally, the correlation analysis was conducted to test for the relationship between the straw covering unevenness by manual and deep sensors, with R (correlation coefficient) of 0.93, RMSE(Root Mean Square Error) of 4.59% and MAPE(Mean of Absolute Percentage Error) of 3.86% with D435i sensor, and with R of 0.915, RMSE of 6.53% and MAPE of 13.85% with Kinect V2, which showed both kinds of RGB-D sensors can acquire the unevenness of straw covering efficiently. The finding can provide a potential way to detect the unevenness of straw coverage and data support for operation evaluation and improvement of no-tillage planter.