Author(s)

Francisco Solís¹, Margarita Hernández¹, Amelia Pérez¹, Carina Toxqui²

¹Autonomous University of Mexico State, Toluca, Mexico.
²Polytechnic University of Tulancingo, Tulancingo, Mexico.

This paper presents two systems for recognizing static signs (digits) from American Sign Language (ASL). These systems avoid the use color marks, or gloves, using instead, low-pass and high-pass filters in space and frequency domains, and color space transformations. First system used rotational signatures based on a correlation operator; minimum distance was used for the classification task. Second system computed the seven Hu invariants from binary images; these descriptors fed to a Multi-Layer Perceptron (MLP) in order to recognize the 9 different classes. First system achieves 100% of recognition rate with leaving-one-out validation and second experiment performs 96.7% of recognition rate with Hu moments and 100% using 36 normalized moments and k-fold cross validation.

Sign Language Recognition, Rotational Signatures, Hu Moments, Multi-Layer Perceptron

Solís, F. , Hernández, M. , Pérez, A. and Toxqui, C. (2014) Static Digits Recognition Using Rotational Signatures and Hu Moments with a Multilayer Perceptron. Engineering, 6, 692-698. doi: 10.4236/eng.2014.611068.