Director, Institute of Agricultural Engineering
ARO - The Volcani Center
Advances and Challenges of Computer Vision in Agriculture
Food needs and food security push agriculture to become more and more technology-driven. Less farmers have to produce food for more people, in a more sustainable and reliable manner. Visual perception has been used for decades as the main feature for decision making in agriculture. Today, digital imagery tends to replace human perception and enable automatic processes with visual feedback. The unstructured environment of agriculture, in conjunction with the high required reliability and accuracy and the low economical margin, makes the application of computer vision in agriculture most challenging. Machine vision systems are incorporated today in field operations like autonomous navigation of agricultural vehicles, in post-harvest processes like grading and sorting of fruits, vegetable and flowers, as well as in aquaculture. Examples and challenges will be presented.