Abstract: Sign Language Recognition is one of the most growing fields of research today. Many new techniques have been developed recently in these fields. Here in this paper, we have proposed a system using Eigen value weighted Euclidean distance as a classification technique for recognition of various Sign Languages of India. The system comprises of four parts: Skin Filtering, Hand Cropping, Feature Extraction and Classification. 24 signs were considered in this paper, each having 10 samples, thus a total of 240 images was considered for which recognition rate obtained was 97%.

Joyeeta Singha and Karen Das, “Indian Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Technique” International Journal of Advanced Computer Science and Applications(IJACSA), 4(2), 2013. http://dx.doi.org/10.14569/IJACSA.2013.040228

@article{Singha2013,
title = {Indian Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Technique},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2013.040228},
url = {http://dx.doi.org/10.14569/IJACSA.2013.040228},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {2},
author = {Joyeeta Singha and Karen Das}
}