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A Real-time Machine Vision Algorithm for Robotic Citrus Harvesting

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2007 ASAE Annual Meeting  073125.(doi:10.13031/2013.23429)
Authors:   M W Hannan, T F Burks, D M Bulanon, (or initial) (or initial)
Keywords:   Citrus, image processing, machine vision, robotic harvesting

Over the last several years there has been a renewed interest in the automation of harvesting of fruits and vegetables. The two major challenges in the automation of harvesting are the recognition of the fruit and its detachment from the tree. In this paper, a machine vision algorithm for the recognition of citrus fruits is presented. The algorithm consists of segmentation, region labeling, size filtering, perimeter extraction and circle detection. Evaluation of the algorithm consisted of images taken inside the canopy (varying lighting condition) and on the canopy surface. Results showed that more than 90% of the fruits were detected in the 110 images tested. In addition, the proposed segmentation was able to deal with varying lighting condition and the circle detection method proved to be effective in detecting fruits in clusters. The development of this algorithm with its capability of detecting fruits in varying lighting condition and occlusion would enhance the overall performance of robotic fruit harvesting.

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