Vegetation Segmentation in Cornfield Images Using Bag of Words
We provide an alternative methodology for vegetation segmentation in cornfield images. The process includes two main steps, which makes the main contribution of this approach: (a) a low-level segmentation and (b) a class label assignment using Bag of Words (BoW) representation in conjunction with a supervised learning framework. The experimental results show our proposal is adequate to extract green plants in images of maize fields. The accuracy for classification is 95.3 % which is comparable to values in current literature.