Water content estimation in leaves using machine learning techniques

Knowing beforehand the amount of water in leaves, may lead to better understanding of ignition in forests. This project is aimed at using machine learning techniques to classify the amount of water present in leaves from several species. To this end, we have a dataset of leaves from Pinus Radiata and Eucalyptus Globulus, with RGB (red, green and blue) images, spectral prints and other information acquired at different drying stages. The goal of this project is to use machine learning techniques to find the water content but only from RGB images, and using the spectral print as benchmark. Dataset will be provied.

Required skills: python/Matlab, machine learning, image processing