On-the-go machine vision sensing of cotton plant geometric parameters: first results

Abstract

Plant geometrical parameters such as internode length (i.e. the distance between successive branches on the main stem) indicate water stress in cotton. This paper describes a machine vision system that has been designed to measure internode length for the purpose of determining real-time cotton plant irrigation requirement. The imaging system features an enclosure which continuously traverses the crop canopy and forces the flexible upper main stem of individual plants against a glass panel at the front of the enclosure, hence allowing images of the plant to be captured in a fixed object plane. Subsequent image processing of selected video sequences enabled detection of the main stem in 88% of frames. However, node detection was subject to a high false detection rate due to leaf edges present in the images. Manual identification of nodes in the acquired imagery enabled measurement of internode lengths with 3% standard error