The efficient management of autonomous
mushroom production plants requires the model of growth rate
of mushrooms. Photos of the plants are used as input for the
growth models, which then predict the development of
individual mushrooms. Recently machine learning techniques
have been successfully applied to create such models. For the
machine learning systems, however, large number of training
samples are required. The training samples include photos of
the plant and also ground truth markers indicating the position
and size of the mushrooms on the photo. In this paper an image
processing system is introduced, which is able to create good
quality ground truth from sequences of images of the plant. The
proposed system can automatically detect the mushroom
positions and sizes on each of the pictures, but also allows user
intervention to minimize the number of detection errors
