Apple Detection for Harvesting Robot Using Computer Vision

Abstract

Development of fruit detection has always been a challenge for a harvesting robot. Detection of fruit in an unregulated environment with change in illuminations affects the harvesting robot's efficiency. This paper presents the improvement of robotic apple harvesting by enhancing apple detection and visibility by handling occlusion in outdoor conditions. For detection of the fruit, we developed an image processing method that is robust to change in illumination and partial occlusion of the apples; we used a stereo camera pair for image acquisition. To detect the fruits efficiently, global thresholding, based on chromaticity approach, is used. The results demonstrated that fruit detection achieved accuracy of 95% in sunny condition and handled partial occlusion of the fruit. This study will be helpful for detecting apples for harvesting robots.