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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Indian Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Technique
Digital Object Identifier (DOI) : 10.14569/IJACSA.2013.040228
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 2, 2013.
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%.
Keywords: Hand Gesture Recognition; Skin Filtering; Human Computer Interaction; Euclidean Distance (E.D.); Eigen value; Eigen vector.
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}
}
