Empirical Analysis of Signature-Based Sign Language Recognition

SUMAIRA KAUSAR ； MUHAMMAD YOUNUS JAVED ； AASIA KHANUM

《Mehran University Research Journal of Engineering and Technology》 33卷4期 (2014/10) Pp. 501-513

摘要

The significance of automated SLR (Sign Language Recognition) proved not only in the deaf community but in various other spheres of life. The automated SLR are mainly based on the machine learning methods. PSL (Pakistani Sign Language) is an emerging area in order to benefit a big community in this region of the world. This paper presents recognition of PSL using machine learning methods. We propose an efficient and invariant method of classification of signs of PSL. This paper also presents a thorough empirical analysis of signature-based classification methods. Six different signatures are analyzed for two distinct groups of signs having total of forty five signs. Signs of PSL are close enough in terms of inter-sign similarity distance therefore, it is a challenge to make the classification. Methodical empirical analysis proves that proposed method deals with these challenges adequately and effectively.

關鍵字

Sign Language Recognition ； Shape Signature ； Pakistani Sign Language