Plant disease detection

Computer vision and machine-learning solutions offer great opportunities for the automatic recognition of sick plants by visual inspection of damaged leaves.

Crop diseases are an important problem, as they cause serious reduction in quantity as well as quality of agriculture products. An automatic plant-disease detection system provides clear benefit in monitoring of large fields, as this is the only approach that provides a chance to discover diseases at an early stage. The solution includes a set of cameras and computing hardware installed on a vehicle. The computer vision core system inspects image flow from cameras, detects diseased leaves, and performs classification. The inspection results can be provided in various ways.

Our research is mostly focused on the following crops:

• Banana
• Corn
• Cotton
• Coffee
• Fruit trees
• Peanut
• Soybean
• Vegetable

Our solution of automated early disease detection is based on an artificial neural network, which is now the most robust technique for image classification. The main advantages of our solution include high processing speed and high classification accuracy. A plant disease recognition system can work as a universal detector, recognizing general abnormalities on the leaves, such as scorching or mold. However, our further research is related to precise recognition of particular diseases. After extensive training on diverse datasets our machine learning model will be capable of distinguishing a large number of different diseases.