  Albanian Sign Language (AlbSL) is relatively new and until now there doesn't
exist a system that is able to recognize Albanian signs by using natural user
interfaces (NUI). The aim of this paper is to present a real-time gesture
recognition system that is able to automatically recognize number signs for
Albanian Sign Language, captured from signer's both hands. Kinect device is
used to obtain data streams. Every pixel generated from Kinect device contains
depth data information which is used to construct a depth map. Hands
segmentation process is performed by applying a threshold constant to depth
map. In order to differentiate signer's hands a K-means clustering algorithm is
applied to partition pixels into two groups corresponding to each signer's
hands. Centroid distance function is calculated in each hand after extracting
hand's contour pixels. Fourier descriptors, derived form centroid distance is
used as a hand shape representation. For each number gesture there are 15
Fourier descriptors coefficients generated which represent uniquely that
gesture. Every input data is compared against training data set by calculating
Euclidean distance, using Fourier coefficients. Sign with the lowest Euclidean
distance is considered as a match. The system is able to recognize number signs
captured from one hand or both hands. When both signer's hands are used, some
of the methodology processes are executed in parallel in order to improve the
overall performance. The proposed system achieves an accuracy of 91% and is
able to process 55 frames per second.
