Machine vision techniques for rose grading

Vincent Steinmetz; Michael Delwiche

doi:10.1117/12.164970

29 November 1993 Machine vision techniques for rose grading

Vincent Steinmetz, Michael Delwiche

Proceedings Volume 2063, Vision, Sensors, and Control for Automated Manufacturing Systems; (1993) https://doi.org/10.1117/12.164970
Event: Optical Tools for Manufacturing and Advanced Automation, 1993, Boston, MA, United States

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.

Citation Download Citation

Vincent Steinmetz and Michael Delwiche "Machine vision techniques for rose grading", Proc. SPIE 2063, Vision, Sensors, and Control for Automated Manufacturing Systems, (29 November 1993); https://doi.org/10.1117/12.164970

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