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Developing Classifier Model for Hand Gesture Recognition for Application of Human Computer Interaction (HCI)

  • Suvarna Nandyal
  • B. SangeetaEmail author
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 38)

Abstract

The hand gesture technique that is regarded as the natural and easy method for the human-machine interaction, has paved way for the development of the multitudes of applications. The hand gestures basically employed in most of the application are either sensor based or the vision based. In case of verbal communication the gesture depiction involves the application of the natural and the bare hand gestures. So the paper proposes a bare hand gesture recognition with the light in variance conditions, involving the image cropping algorithm in the preprocessing, considering only the region of interest. The mapping of the image oriented histogram is primarily done utilizing the Euclidean distance method and further supervised neural network are trained using the images mapped, to have a better recognition of images with the same gestures under different light intensities.

Keywords

Hand image segmentation Light invariant hand gesture recognition Fingertips detection Bent fingers’ angles calculation Both hands’ angles calculation 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.CSE DepartmentPDA College of EngineeringKalaburgiIndia
  2. 2.PDA College of EngineeringKalaburgiIndia

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