Volume Controlling with Hand Gesture

Authors

  • Sonali Thanambir  Department of Computer Engineering, Zeal College of Engineering & Research Pune, Maharashtra, India
  • Abhishek Shete  Department of Computer Engineering, Zeal College of Engineering & Research Pune, Maharashtra, India
  • Trupti Mane  Department of Computer Engineering, Zeal College of Engineering & Research Pune, Maharashtra, India
  • Harshada Gawade  

Keywords:

Hand gesture, Recognition, Detection, Diagonal Sum, Pre-processing, Feature extraction, Skin Modeling, Labeling

Abstract

The project introduces an application using computer vision for Hand gesture recognition. A camera records a live video stream, from which a snapshot is taken with the help of interface. The system is trained for each type of count hand gestures (one, two, three, four, and five) at least once. After that a test gesture is given to it and the system tries to recognize it. A research was carried out on a number of algorithms that could best differentiate a hand gesture. It was found that the diagonal sum algorithm gave the highest accuracy rate. In the preprocessing phase, a self-developed algorithm removes the background of each training gesture. After that the image is converted into a binary image and the sums of all diagonal elements of the picture are taken. This sum helps us in differentiating and classifying different hand gestures. Previous systems have used data gloves or markers for input in the system. I have no such constraints for using the system. The user can give hand gestures in view of the camera naturally. A completely robust hand gesture recognition system is still under heavy research and development; the implemented system serves as an extendible foundation for future work.

References

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Published

2022-04-30

Issue

Section

Research Articles

How to Cite

[1]
Sonali Thanambir, Abhishek Shete, Trupti Mane, Harshada Gawade "Volume Controlling with Hand Gesture " International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 9, Issue 2, pp.492-499, March-April-2022.