A fruit recognition method for automatic harvesting

Date of Award


Publication Type

Master Thesis


Electrical and Computer Engineering



Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.


Automation of harvesting is always one of the hottest topics in greenhouse operation. But before this, a reliable method of identifying mature fruit clusters on plants is required. This thesis presents a method to detect and recognize mature tomato fruit clusters on a complex-structured tomato plant containing clutter and occlusion in a tomato greenhouse. A color stereo vision camera is applied as the vision sensor. The proposed method performs a 3D reconstruction with the data collected by the stereo camera to create a 3D environment for further processing. The Color Layer Growing (CLG) method is introduced to segment the mature fruits from the leaves, stalks, background and noise. Target fruit clusters can then be located by depth segmentation. The experimental data was collected from a tomato greenhouse and the method is justified by the experimental results.