Automated detection and counting of grape bunches using a farmer robot

This paper describes a novel image acquisition and processing framework to detect and count grape bunches along vineyard rows, using RGB and depth data acquired in the field by a farmer robot. The proposed pipeline starts with a semantic image segmentation module that uses a pre-trained convolutional neural network to separate fruit from non-fruit regions. Areas pertaining to fruits are then further processed using a depth gradient-based clustering algorithm to detect and separate single grape bunches. Experiments performed in a commercial vineyard are presented showing that, despite the low quality of the input images, the proposed approach is able to correctly detect and count grape clusters with good accuracy.