Czech Sign Language Single Hand Alphabet Letters Classification

The paper deals with the classification of images of Czech sign language alphabet, single handed version in particular, without diacritics. The classification is performed by convolution neural network using TensorFlow computational library. Network topology, data acquisition and automatic labelling and obtained results are described in the paper. The accuracy on the test data - captured images of a person not previously seen by the network – was over 87%.