Identification of Plant Textures in Agricultural Images by Principal Component Analysis

In precision agriculture the extraction of green parts is a very important task. One of the biggest issues, when it comes to computer vision, is image segmentation, which has motivated the research conducted in this work. Our goal is the segmentation of vegetative and soil parts in the images. For this proposal a novel method of segmentation is defined in which different vegetation indices are calculated and through the reduction of components by principal component analysis (PCA) we obtain an enhanced greyscale image. Finally, by Otsu thresholding, we binarize the grayscale image isolating the green parts from the other elements in the image.