Static Digits Recognition Using Rotational Signatures and Hu Moments with a Multilayer Perceptron


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.

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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.

Conflicts of Interest

The authors declare no conflicts of interest.


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