• Aleksejs Zorins Rezekne Academy of Technology (LV)
  • Peter Grabusts Rezekne Academy of Technology (LV)



artificial neural networks, centre of gravity, classification, hand gesture, sign language recognition


There is a lack of automated sign language recognition system in Latvia while many other countries have been already equipped with such a system. Latvian deaf society requires support of such a system which would allow people with special needs to enhance their communication in governmental and public places. The aim of this paper is to recognize Latvian sign language alphabet using classification approach with artificial neural networks, which is a first step in developing integral system of Latvian Sign Language recognition. Communication in our daily life is generally vocal, but body language has its own significance. It has many areas of application like sign languages are used for various purposes and in case of people who are deaf and dumb, sign language plays an important role. Gestures are the very first form of communication. The paper presents Sign Language Recognition possibilities with centre of gravity method. So this area influenced us very much to carry on the further work related to hand gesture classification and sign’s clustering.


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How to Cite

A. Zorins and P. Grabusts, “LATVIAN SIGN LANGUAGE RECOGNITION CLASSIFICATION POSSIBILITIES”, ETR, vol. 2, pp. 185–188, Jun. 2017, doi: 10.17770/etr2017vol2.2653.