Automatic Mexican sign language and digits recognition using normalized central moments

Francisco Solís; David Martínez; Oscar Espinosa; Carina Toxqui

doi:10.1117/12.2236353

27 September 2016 Automatic Mexican sign language and digits recognition using normalized central moments

Francisco Solís, David Martínez, Oscar Espinosa, Carina Toxqui

Proceedings Volume 9971, Applications of Digital Image Processing XXXIX; 997103 (2016) https://doi.org/10.1117/12.2236353
Event: SPIE Optical Engineering + Applications, 2016, San Diego, California, United States

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.

Citation Download Citation

Francisco Solís, David Martínez, Oscar Espinosa, and Carina Toxqui "Automatic Mexican sign language and digits recognition using normalized central moments", Proc. SPIE 9971, Applications of Digital Image Processing XXXIX, 997103 (27 September 2016); https://doi.org/10.1117/12.2236353

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