Machine Learning Based Approach for Weed Detection in Chilli Field Using RGB Images

Smart farming has become imperative these days due to competition, and use of Unmanned Aerial Vehicle (UAV) imagery is becoming an integral part of the process. Machine learning techniques have been successfully applied to capture UAV imagery of various spectral bands to identify weed infestations. Identification of weeds in chilli crop is a challenging task. In this paper, RGB images captured by drones have been used to detect weed in chilli field. This task has been addressed through orthomasaicking of images, feature extraction, labelling of images to train machine learning algorithms, and use of unsupervised learning with random forest for classification. MATLAB has been used for all computations and out-of-bag accuracy achieved for identifying weeds is 96\(\%\).