Methodology for agave plants recognition based on superpixels segmentation and drone images

The tequila and agave culture are important symbols of the national identity in Mexico. In the last decade, the production of tequila has increased and improved the care of Tequilana Webber Blue Agave. In this paper, we introduce a methodology based on the use of Unmanned Aerial Vehicles (UAV) as drones, image processing techniques and machine learning approaches for the detection of agave plants. Several landscape images of agave crops are collected from the Romita region in Guanajuato state. These images are processed to obtain orthomosaics which allow us to study all the target region of the agave crops. The orthomosaics are segmented using superpixels techniques in order to define features which allow us to recognise the agave plants. For experimental purposes we compare five segmentation methods in order to evaluate the performance for the detection of agave plants. Random Forest Classifier Algorithm (RFC) is implemented for classification purposes. Our proposal achieves 97% of accuracy to detect the agave plants.