optical sorting of sprouts for double capacity machines


Deman NV
Passendale, Belgium

computer vision

machine vision

artificial intelligence

industrial IoT & data analytics



optical sorting for agro machinery

product inspection & selection at high speed


Deman nv is a family company that is at its third generation. The company was founded as a local forge for local farmers by Marcel Deman. 

Nowadays Deman nv is a well-known company in the field of agro machinery. Through expertise and craftmanship Deman nv can build and repair a wide spread of machines and metal constructions. In 1971 the company started making its first Brussels sprout harvester based on their own design and expertise.

"Our software was not working properly and jeopardized overall performance. With the help of vintecc we were able to re-engineer the machinesoftware from top to bottom."

Pieter-Jan Deman

Pieter-Jan Deman

Owner, DemanNV


Deman nv had developed a mechanically working sorting machine. The software nevertheless was not working properly and jeopardized overall performance. vintecc was pulled into the project and together with Pieter-Jan Deman we re-engineered the machine from top to bottom.


1 correct hardware selection is crucial
  • Selection of the correct hardware components such as lighting with even distribution, camera’s, etc. pointed out to be very crucial
  • Problems such as over- or underlighting make the sensor input (camera’s) hard to use or even not useful for the algorithms at all. Also, an even distribution of the light is necessary in order to make the same evaluation regardless of the sprout’s position in the image.
  • Finally, a correct synchronisation between camera and lighting was required to capture good quality images to be processed by our algorithms. Disturbances of sunlight or other surrounding light sources were accounted for.
Effect of overlighting(left) and uneven distribution of light (right)
2 training an AI-algorithm
  • For image processing, an algorithm was trained to make a correct distinction between good and bad sprouts.
Outcome of trained algorithm
3 ejection of sprouts at high speed
  • Bad sprouts needed to be ejected from the main stream.
  • Taking into account mass densities and feedback of high speed camera images, the trajectories during sprout drop from image acquisition to the ejection fingers could be estimated. 
  • This was important as for successful ejection, only a margin of 5msec could be tolerated.
High speed ejection of sprouts
4 user friendly operator HMI-interface
  • Finally, the importance of a userfriendly operator interface cannot be underestimated. 
  • This interface had to be simple, easily configurable and well understood by any operator. We succeeded in giving the operator a sufficient level of control by changing only one parameter. 
  • Additionally, a replay function helped the operator to evaluate parameter changes in an easy and transparant way. On top, the operator gets much additional information, such as machine load, performance and throughput based on which new insights are gained.
Main view of the web interface


1 outperforming the competition by far
  • The project resulted in a performant, modular and cost efficient sorting machine for Brussels sprouts which can be built upon harvesters or used stationary. The machine outperforms competition by far. 
  • A result of 2.99% false rejects and 0.69% false accepts was recorded whereas market standard accepts up to 5%.
2 entering a new market segment
  • The project allowed Deman nv to enter the market of vision based sorting machines. Double capacity sorting machines are now widely installed in the packaging lines of customers.
Double capacity sorting machine