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Vision-based hand gesture recognition of alphabets, numbers, arithmetic operators and ASCII characters in order to develop a virtual text-entry interface system

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Abstract

Hand gesture recognition can substitute the use of text-entry interface for human computer interaction. However, it is a challenging task to develop a virtual text-entry interface covering a large number of gesture-based characters. In this paper, 18 new ASCII printable characters have been introduced along with some of the previously introduced characters [A–Z alphabets, 0–9 numbers and four arithmetic operators (add, minus, multiply, divide)]. In addition to some of the efficient existing features, three new features of 15 dimensions have been incorporated to enhance the performance of the system, which are normalized distance between direction extreme, close figure test and direction change ratio. These features are measured for single-stroke as well as multistroke gestures. An experimental analysis has been carried out for selection of optimal features using the statistical analysis techniques such as one-way analysis of variance test, Kruskal–Wallis test, Friedman test in combination with incremental feature selection technique. Furthermore, a comparative study has been carried out for classification of 58 gestures with the new list of features. A comparative analysis has been performed using five classifiers, namely SVM, kNN, Naïve Bayes, ANN and ELM. It has been observed that maximum accuracy achieved using the combination of existing and proposed features is 96.95%, as compared to 94.60% accuracy achieved using existing features for classification of 58 gestures.

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Acknowledgements

The authors acknowledge the Speech and Image Processing Laboratory under Department of ECE at National Institute of Technology, Silchar, India, for providing all necessary facilities to carry out the research work.

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Authors and Affiliations

  1. Department of ECE, NIT Silchar, Silchar, India

    Songhita Misra, Joyeeta Singha & R. H. Laskar

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  1. Songhita Misra
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  2. Joyeeta Singha
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  3. R. H. Laskar
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Correspondence to Songhita Misra.

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The project is not funded by any organization. The authors declare that they have no conflict of interest.

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Misra, S., Singha, J. & Laskar, R.H. Vision-based hand gesture recognition of alphabets, numbers, arithmetic operators and ASCII characters in order to develop a virtual text-entry interface system. Neural Comput & Applic 29, 117–135 (2018). https://doi.org/10.1007/s00521-017-2838-6

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