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

DOI: 10.4236/eng.2014.611068   PDF   HTML   XML   4,084 Downloads   4,679 Views   Citations


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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