Illumination invariant segmentation of vegetation for time series wheat images based on decision tree model
We propose a new model based on decision tree to segment vegetation in RGB images. The model performs well even an image include shadowed and specularly reflected parts. The model does not require thresholding in each image. This model is advantageous for a time series images under varying natural light conditions.
natural light condition vegetation segmentation non-thresholding machine learning specular reflection