Phytosanitary treatment is one of the most critical operations in vineyard management.
Ideally, the spraying system should treat only the canopy, avoiding drift, leakage, and wasting of
product where leaves are not present: variable rate distribution can be a successful approach, allowing
the minimization of losses and improving economic as well as environmental performances. The
target of this paper is to realize a smart control system to spray phytosanitary treatment just on
the leaves, optimizing the overall costs/benefits ratio. Four different optical-based systems for leaf
recognition are analyzed, and their performances are compared using a synthetic vineyard model. In
the paper, we consider the usage of three well-established methods (infrared barriers, LIDAR 2-D
and stereoscopic cameras), and we compare them with an innovative low-cost real-time solution
based on a suitable computer vision algorithm that uses a simple monocular camera as input. The
proposed algorithm, analyzing the sequence of input frames and exploiting the parallax property,
estimates the depth map and eventually reconstructs the profile of the vineyard’s row to be treated.
Finally, the performances obtained by the new method are evaluated and compared with those of the
other methods on a well-controlled artificial environment resembling an actual vineyard setup while
traveling at standard tractor forward speed
