Published Oct 26, 2010



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Nelson Balsero

Diego Botero

Juan Zuluaga

Carlos Alberto Parra-Rodríguez

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Abstract

In this paper we present the development of an electronic system able to recognize, in real time, a set of twelve manual gestures carried out by a person with one of his hands in a controlled illumination and background scene. The implemented system shows rotational, translational and scale change robustness. The system is intended to evaluation platform ADSP Blackfin 533 Ez Kit Lite. As a final step, in the Blackfin’s platform, we propose a view option in a display of the associated letter to the recognized gesture. In the personal computer we present an illustration tool intended to show the results in different steps of the proposed algorithm. We obtained an efficient system for human machine interaction and future applications intended to enable the interaction of deaf and mute people with the population in general.

Keywords

recognition and interpretation of images, humanmachine interaction in real time, Blackfin 533 processorreconocimiento e interpretación de imágenes, interacción hombre-máquina en tiempo real, procesador Blackfin 533

References
ADSP-BF533 Blackfin Processor Hardware Reference, Rev. 3.0. Analog Devices, s.d.
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Intel® Software Products Open Source Intel Open Source Computer Vision Library Reference Manual Diciembre 2004. Disponible en la dirección electrónica http://www.intel.com/research/mrl/research/opencv.
Lienhart, R., Maydt, J. “An Extended Set of Haar-like Features for Rapid Object Detection”. IEEE ICIP, 2002.
Viola, P., Jones, M.J. “Rapid Object Detection using a Boosted Cascade of Simple Features”. IEEE CVPR, 2001.
How to Cite
Balsero, N., Botero, D., Zuluaga, J., & Parra-Rodríguez, C. A. (2010). Interacción hombre-máquina usando gestos manuales en texto real. Ingenieria Y Universidad, 9(2). Retrieved from https://revistas.javeriana.edu.co/index.php/iyu/article/view/903
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Articles

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