
Proceedings Paper
Automatic Mexican sign language and digits recognition using normalized central momentsFormat | Member Price | Non-Member Price |
---|---|---|
$17.00 | $21.00 |
Paper Abstract
This work presents a framework for automatic Mexican sign language and digits recognition based on computer vision
system using normalized central moments and artificial neural networks. Images are captured by digital IP camera, four
LED reflectors and a green background in order to reduce computational costs and prevent the use of special gloves. 42
normalized central moments are computed per frame and used in a Multi-Layer Perceptron to recognize each database.
Four versions per sign and digit were used in training phase. 93% and 95% of recognition rates were achieved for
Mexican sign language and digits respectively.
Paper Details
Date Published: 27 September 2016
PDF: 5 pages
Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 997103 (27 September 2016); doi: 10.1117/12.2236353
Published in SPIE Proceedings Vol. 9971:
Applications of Digital Image Processing XXXIX
Andrew G. Tescher, Editor(s)
PDF: 5 pages
Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 997103 (27 September 2016); doi: 10.1117/12.2236353
Show Author Affiliations
Francisco Solís, Univ. Autónoma del Estado de México (Mexico)
David Martínez, Univ. Autónoma del Estado de México (Mexico)
David Martínez, Univ. Autónoma del Estado de México (Mexico)
Oscar Espinosa, Univ. Autónoma del Estado de México (Mexico)
Carina Toxqui, Univ. Politécnica de Tulancingo (Mexico)
Carina Toxqui, Univ. Politécnica de Tulancingo (Mexico)
Published in SPIE Proceedings Vol. 9971:
Applications of Digital Image Processing XXXIX
Andrew G. Tescher, Editor(s)
© SPIE. Terms of Use
