The EMVA Young Professional Award 2013 has been won by Ruud Barth, computer vision scientist at Wageningen University and Research Center in the Netherlands, for his computer vision application for the automatic registration, recognition and analysis of broccoli for robotised harvesting.
The EMVA Young Professional Award is an annual award to honour the outstanding and innovative work of a student or a young professional in the field of machine vision or image processing. It is the goal of the European Machine Vision Association to further support innovation in the machine vision industry, to contribute to the important aspect of dedicated machine vision education and to provide a bridge between research and industry.
With the annual Young Professional Award, the EMVA intends to specifically encourage students to focus on challenges in the field of machine vision and to apply latest research results and findings in computer vision to the practical needs of the industry. Barth, who is 25 years old, has finished his master degree in artificial intelligence in 2011 with Cum Laude at Radboud University Nijmegen, The Netherlands.
The work Barth was awarded for lies in the addition of computer vision based selectivity to the harvesting process of broccoli. Broccoli grows at different speeds, resulting in high variance of crop size. Currently all broccoli is harvested with a robot in one pass. The result is a suboptimal harvest, containing a high share of broccoli that is either too small or too big.
The innovation solves this problem by adding industrial cameras to the harvesting robot, which produce high-resolution images of the broccoli during the harvest. Image analysis then performs a set of crop-specific texture functions in order to separate the broccoli from the rest of the crop and in a next step to determine the position and size of the broccoli.
Using this information, it can be calculated whether the broccoli is ready to be harvested. If this is the case, a signal with a location of the broccoli is sent to the harvesting unit of the robot. By using the new system, food waste can be reduced while yields can be increased.
