Pose recognition using cross correlation for static images of Urdu sign language

Sign language recognition has been an active area of research for around two decades and numerous different sign languages have been extensively studied in order to design reliable sign language recognition systems. Urdu, the national language of Pakistan, and its corresponding sign language, has so far been largely neglected by the academia, which is one of the reasons, it has been chosen for developing an Urdu sign language recognition system. A comprehensive database of static images depicting the signs for different Urdu alphabets is being used as reference and input images are being compared to perform Urdu alphabet recognition. Cross-correlation technique is being used for image registration between input image and images from the database to find the closest match. The tolerance level ensures a trade-off between computational complexity and accuracy of the match between set of images. The algorithm tests on the images have been around 75% successful and attempts are being made for more efficient and robust performance.