TITLE:
Static Digits Recognition Using Rotational Signatures and Hu Moments with a Multilayer Perceptron
AUTHORS:
Francisco Solís, Margarita Hernández, Amelia Pérez, Carina Toxqui
KEYWORDS:
Sign Language Recognition, Rotational Signatures, Hu Moments, Multi-Layer Perceptron
JOURNAL NAME:
Engineering,
Vol.6 No.11,
October
28,
2014
ABSTRACT: 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.