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Feature Extraction Technique for Vision-Based Indian Sign Language Recognition System: A Review

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Computational Methods and Data Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1227))

Abstract

Vision-based sign language recognition system is an emerging research area in human-computer interaction (HCI). It has been proved as a powerful communication tool for deaf and mute society, irrespective of geographical differences. Automatic sign language recognition system works broadly in three phases namely image pre-processing, feature extraction and classification of gestures. The output of the feature extraction phase is crucial for various classifiers. This paper presents a comprehensive review of feature extraction techniques used in vision-based sign language recognition system. A taxonomy of currently used techniques for feature extraction has been presented. The paper concludes by presenting future direction in feature extraction technique for Indian sign language (ISL).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Maharishi Markandeshwar (Deemed to be University), Ambala, Haryana, India

    Akansha Tyagi & Sandhya Bansal

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  1. Akansha Tyagi
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  2. Sandhya Bansal
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Correspondence to Akansha Tyagi .

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Editors and Affiliations

  1. School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India

    Vijendra Singh

  2. Department of Electrical and Computer Engineering, University of Dayton, Dayton, OH, USA

    Vijayan K. Asari

  3. Department of Computer Science and Engineering, SRM University Delhi-NCR, Sonepat, Haryana, India

    Sanjay Kumar

  4. Department of Computer Science and Engineering, Chandigarh College of Engineering and Technology, Chandigarh, Punjab, India

    R. B. Patel

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Tyagi, A., Bansal, S. (2021). Feature Extraction Technique for Vision-Based Indian Sign Language Recognition System: A Review. In: Singh, V., Asari, V., Kumar, S., Patel, R. (eds) Computational Methods and Data Engineering. Advances in Intelligent Systems and Computing, vol 1227. Springer, Singapore. https://doi.org/10.1007/978-981-15-6876-3_4

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