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Título del libro: Proceedings Of The 2012 International Conference On Artificial Intelligence, Icai 2012
Título del capítulo: Contour object generation in object recognition manufacturing tasks

Autores UNAM:
JUAN MARIO PEÑA CABRERA; VICTOR MANUEL LOMAS BARRIE; ROMAN VICTORIANO OSORIO COMPARAN; HUMBERTO GOMEZ NARANJO;
Autores externos:

Idioma:
Inglés
Año de publicación:
2012
Palabras clave:

Automated manufacturing process; Binarized images; Contour information; Fuzzy ARTMAP; Industrial environments; Manufacturing tasks; Neural network model; Robust methods; Algorithms; Artificial intelligence; Computer vision; Field programmable gate arrays (FPGA); Manufacture; MATLAB; Robots; Vision; Object recognition


Resumen:

The article presents a method for obtaining the contour of an object in real time from not binarized images and for objects that can be assembled on line in automated manufacturing processes. The contour information is integrated into a descriptive vector called [BOFnew], which is used by a neural network model of the type FuzzyARTMAP to test the feasibility of the method using the generated contour to learn of the object and then recognize it later To this end, it requires a fast and robust method to acquire process and communicate to a robot the information about positioning and orientation of an object for assembly purposes. The used algorithm and its simulation was developed in MatLab 7.0. Having this method for object recognition manufacturing tasks improves this methodology and allows the implementation of these algorithms in FPGA 's, which gives in manufacturing cell a real possibility performance demanded by industrial environments.


Entidades citadas de la UNAM: