Machine vision is part of many automation and robotics applications used in agriculture. Tractors drive autonomously, drones or Unmanned Aerial Vehicles record the condition of the soil, robots assist in milking, feeding, and harvesting. Inspection of seeds and produce for quality and grade is also performed with machine vision technologies.
Productivity, efficiency, and sustainability are some of the critical factors driving the adoption of automation technology in today's agriculture industry.
Challenges of Today's Agriculture
Feeding the growing world population
Protection of the environment
Fulfillment of governmental regulations
Compensation of fast changing weather conditions
Limited resources like water and agricultural areaHigh production and labor cost
The flexibility and high quality of MVTec software contribute decisively to your sustainable economic success. The software architecture allows fast development of all kind of machine vision applications and thus the development of new automation solutions. This results in cost savings and an improved time to market for you.
Best-Practice-Solution: Efficient Plant Protection with MVTec
Plant protection is an important component of crop cultivation to ensure high yields and best quality. Growing objections and increasingly strict regulations of traditional protection methods are challenges that have to be faced. Therefore, it is necessary for crop protection products to be put to particularly efficient use. With the help of machine vision, it is possible to distinguish between crops and weeds in real time and to precisely apply the agent as you can see in the following video:
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As shown in the video an industrial camera (multispectral image acquisition) is mounted on the sprayer and takes pictures of the plantation. The camera sends the data to an embedded device. This device runs machine vision software by MVTec and controls the application. The software uses deep-learning-based object detection to identify weeds between crops and gives the system the impulse to precisely apply the herbicide to the identified weeds.
The advantages are evident:
Targeted application reduces the environmental impact
Resources are used cost-efficiently
The result are high yields and best quality in harmony with nature conservation regulations and consumer wishes
Best-Practice-Solution: Automated Monitoring and Harvesting with MVTec
The automation of processes in greenhouses using machine vision technologies makes it possible to better meet the increasing demand and requirements for quality, hygiene, and food safety. Automation compensates for the lack of qualified workers and promotes efficient and sustainable crop production in greenhouses. With the help of machine vision, harvesting robots precisely detect, classify and harvest ripe crops as you can see in the following video:
The video shows a greenhouse harvesting robot monitoring and harvesting pepper plants. A 3D stereo camera creates a 3D point cloud of the pepper plant. Based on this data, the software generates a 3D scene to locate the single peppers. Deep learning technologies are used to classify the exact degree of ripeness and plant health. After the software has identified the best gripping and cutting point, the robot can harvest the peppers.
The advantages are evident:
Precise harvest time ensures best quality
High availability reduces personnel bottlenecks
Reliable and objective monitoring helps ensure early detection of diseases and thus reduces the use of harmful substances
Shaping the Future of Agriculture with MVTec on Campus
A Program to Improve Machine Vision in Agricultural Research and Teaching
With the MVTec on Campus program we aim to pass on our experience and expertise and to help promote research on innovative machine vision technologies in agriculture. In order to accelerate research results, we strive for a mutually supportive partnership with universities. Therefore we are providing professors and lecturers with HALCON software free of charge.