Determination of Plant Height for Crop and Weed Discrimination by Using Stereo Vision System

Abstract

The stereo vision experiments were conducted under the laboratory conditions by using LabVIEW programming language. An artificial crop plant and six types of artificial weed samples were used in the experiments. The information related to the plant height is a relevant feature to classify the crop plant and weed, especially in the early growth stage. A binocular stereo vision system was established by using two identical webcams with parallel optical axes and a laptop computer to discriminate the artificial crop plant and six types of weeds correctly. The calculated depth values were compared with the physical measurements for the same points. While the measurement error of the system was less than 3.50% for the artificial crop plant, it was less than 4.20% for six artificial weed samples. There were also strong, positive and significant linear correlations between the stereo vision and physical height measurements for artificial crop plant and weed samples. Calculated correlation values (R2) between the stereo vision and physical height measurements were 0.962 for the artificial crop plant and 0.978 for the artificial weed samples, respectively. That stereo vision system could be integrated into automatic spraying systems for intra-row spraying applications.