Fourier descriptors and neural networks far shape classification

There is a pressing need for sign language to English translation capability to supplement the shortage of sign language interpreters and to provide an aid for training. A modular hybrid design is underway to apply various techniques, including neural networks, in the development of a translation system that can facilitate communication between deaf and hearing people as part of an overall system to automatically translate American sign language to spoken English. The key features to be analyzed are hand motion, hand location with respect to the body, and handshape. A neural network is used to recognize and classify alphanumeric handshapes using Fourier descriptor coefficients as an input vector. The algorithm is described and results shown for applying this technique to experimental images