A Solution for Vegetation Analysis, Separation and Geo-location of Management Zones using Aerial Images by UAVs - Santos, Suzane; Melo, Joanacelle; Constantino, Renato; Brito, Alisson (Anais do Simpósio Brasileiro de Engenharia de Sistemas Computacionais (SBESC); 2019: Anais do IX Simpósio Brasileiro de Engenharia de Sistemas Computacionais, 2019)
This work presents an automatic system of vegetation monitoring and separation in management zones using aerial images captured by Unmanned Aerial Vehicles (UAVs). The system analyzes crop images and divides them into regions identified by color for easy viewing of problem areas. To do so, it uses the NDVI vegetation index and the K-means clustering algorithm. Besides, the system allows locating each management zone through geographical coordinates. The algorithm was optimized, allowing its execution in embedded systems. As results, processing times of approximately 7s were achieved for an image with 9,387,360 pixels using a conventional computer, and 5s for an image of 493,500 pixels using an embedded system.