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Proceedings Paper

Machine vision techniques for rose grading
Author(s): Vincent Steinmetz; Michael Delwiche
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Paper Abstract

A machine vision system was developed to inspect roses, and assign grades similar to those used by human graders. Illumination and image processing techniques were developed to extract the main features used by human vision. These features were identified as stem length, diameter and straightness, and bud color and maturity (i.e., openness). Illumination techniques include the design of an inspection chamber and the choice of proper light source. Image analysis includes the development of algorithms for image understanding. Supervised learning was used to classify roses.

Paper Details

Date Published: 29 November 1993
PDF: 12 pages
Proc. SPIE 2063, Vision, Sensors, and Control for Automated Manufacturing Systems, (29 November 1993); doi: 10.1117/12.164970
Show Author Affiliations
Vincent Steinmetz, Cemagref (France)
Michael Delwiche, Univ. of California/Davis (United States)


Published in SPIE Proceedings Vol. 2063:
Vision, Sensors, and Control for Automated Manufacturing Systems
Scott S. Breidenthal; Alan A. Desrochers, Editor(s)

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