Authors:
Vincent Muracciole
1
;
Patrick Plainchault
1
;
Dominique Bertrand
2
and
Maria Rosaria Mannino
2
Affiliations:
1
INRA; ESEO;LISA; GEVES-SNES, Université d’Angers; CER ESEO, France
;
2
ENITIAA-INRA, Sensométrie - Chimiométrie; GEVES-SNES, France
Keyword(s):
Machine vision, computer vision, seed identification, grain quality, seed quality, embedded systems.
Related
Ontology
Subjects/Areas/Topics:
Control and Supervision Systems
;
Image Processing
;
Informatics in Control, Automation and Robotics
;
Modeling, Simulation and Architectures
;
Robotics and Automation
;
Vision, Recognition and Reconstruction
Abstract:
Purity analysis and determination of other seeds by number are still made manually. It is a repetitive task based upon visual analysis. Our work objective is to create and use a simple and quick automated system to do this task. A first step of this machine has been reached by validating the image acquisition and feeding process. The principle of this machine is based on a seeds fall with stroboscopic effect image acquisition. This article presents the first step of creating a dedicated and autonomous machine which combines embedded constraints and real time processes.