27 September 2016 Automatic Mexican sign language and digits recognition using normalized central moments
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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.
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Francisco Solís, Francisco Solís, David Martínez, David Martínez, Oscar Espinosa, Oscar Espinosa, Carina Toxqui, 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); doi: 10.1117/12.2236353; https://doi.org/10.1117/12.2236353
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