By using a computer vision-controlled system to map terrain and identify the size and location of rocks embedded in the soil, the heavy lifting is done by automated machinery which saves farmers a lot of time and money.
Image processing with cameras and AI enables applications that were previously unthinkable. In agriculture, for example, it supports the optimal application of fertilizers, the visual monitoring of products and growth phases, and the processing of harvested crops.
Anyone who wants to realize applications in which objects with a wide variety of characteristics - such as vegetables or fruit - are to be reliably recognized, cannot afford to ignore image processing with artificial intelligence.
Digitized and automated processes are becoming increasingly important in modern agricultural enterprises. Machine vision methods play a key role here. Among other things, they can be used for a variety of precision farming applications.
Stuttgart-based technet GmbH has developed a system that uses a USB 3 uEye CP industrial camera from IDS to capture the contours and surface parameters of the parasites and determines the curvature energies of individual larvae from these data.
Multispectral cameras capture spectral signatures much like a thermometer measures the temperature of the human body. Changes in plant reflectance indicate stress, but additional information is required to identify the cause.
This is today's agriculture: Tractors drive autonomously and the cultivation of fields can be carried out precisely and plant-specifically. Drones record the condition of the soil and crops from the air. Robots assist in milking, feeding, and monitoring animals. MVTec's machine vision software helps farmers realize these and other applications and confidently face many of today's modern agriculture challenges.