Ripe tomato extraction for a harvesting robotic system

Abstract

A robotic system for harvesting tomatoes in greenhouses is designed. Effective recognition of ripen tomatoes from complex background is the key technology of the harvesting robotic system. In this work, the color feature of ripen tomatoes is employed. The ripen tomato is segmented by K-means clustering using the L*a*b* color space. To extract a single integrity ripen tomato, mathematical morphology method is used to denoise and handle the situations of tomato overlapping and shelter. Experimental results show the effectiveness of the proposed method.