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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Indian Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Technique

Author 1: Joyeeta Singha Author 2: Karen Das
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 4, No. 2 · Published 2013 · Cited by 20

DOI: https://doi.org/10.14569/IJACSA.2013.040228

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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.

How to Cite this Article

Singha, J., & Das, K. (2013). Indian Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Technique. International Journal of Advanced Computer Science and Applications, 4(2). https://doi.org/10.14569/IJACSA.2013.040228

Singha, Joyeeta, and Karen Das. "Indian Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Technique." International Journal of Advanced Computer Science and Applications, vol. 4, no. 2, 2013, https://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},
  volume    = {4},
  number    = {2},
  year      = {2013},
  publisher = {The Science and Information Organization},
  author    = {Joyeeta Singha and Karen Das},
  doi       = {10.14569/IJACSA.2013.040228},
  url       = {https://doi.org/10.14569/IJACSA.2013.040228}
}

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