Share Email Print
cover

Proceedings Paper

Detection of oranges from a color image of an orange tree
Author(s): Arthur Robert Weeks; A. Gallagher; J. Eriksson
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The progress of robotic and machine vision technology has increased the demand for sophisticated methods for performing automatic harvesting of fruit. The harvesting of fruit, until recently, has been performed manually and is quite labor intensive. An automatic robot harvesting system that uses machine vision to locate and extract the fruit would free the agricultural industry from the ups and downs of the labor market. The environment in which robotic fruit harvesters must work presents many challenges due to the inherent variability from one location to the next. This paper takes a step towards this goal by outlining a machine vision algorithm that detects and accurately locates oranges from a color image of an orange tree. Previous work in this area has focused on differentiating the orange regions from the rest of the picture and not locating the actual oranges themselves. Failure to locate the oranges, however, leads to a reduced number of successful pick attempts. This paper presents a new approach for orange region segmentation in which the circumference of the individual oranges as well as partially occluded oranges are located. Accurately defining the circumference of each orange allows a robotic harvester to cut the stem of the orange by either scanning the top of the orange with a laser or by directing a robotic arm towards the stem to automatically cut it. A modified version of the K- means algorithm is used to initially segment the oranges from the canopy of the orange tree. Morphological processing is then used to locate occluded oranges and an iterative circle finding algorithm is used to define the circumference of the segmented oranges.

Paper Details

Date Published: 18 October 1999
PDF: 12 pages
Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); doi: 10.1117/12.365846
Show Author Affiliations
Arthur Robert Weeks, Univ. of Central Florida (United States)
A. Gallagher, Univ. of Central Florida (United States)
J. Eriksson, Univ. of Central Florida (United States)


Published in SPIE Proceedings Vol. 3808:
Applications of Digital Image Processing XXII
Andrew G. Tescher, Editor(s)

© SPIE. Terms of Use
Back to Top