HANDVIBE: HAND GESTURE VOLUME AND BRIGHTNESS CONTROL
Sudhanshu Ranshevare1, Nilesh Dusane2, Harsh Kapadnis3, Anjali Tajane4, Prof. S. B. Patil5
*1,2,3,4 students Department of Computer Engineering, Jawahar Education Society’s Institute Of Technology, Management And Research, Nashik Maharashtra, India.
*5 Professor, Department of Computer Engineering, Jawahar Education Society’s Institute Of Technology, Management And Research, Nashik Maharashtra, India.
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Abstract:- Gesture Recognition has become increasingly relevant in the field of human-computer interaction, as it is a natural way to convey information. We aim to create a system that can identify specific human gestures and utilize them to transmit information for device control. This enables users to operate a computer by performing a specific gesture in front of the camera. The below approach can detect multiple hands simultaneously, that is left and right, each having its own purpose. It is detected by a standard webcam, and requires no extra equipment. The left hand is responsible in controlling the brightness and the right hand will be responsible for controlling the volume. Here we have used different computer vision techniques which includes border detection, and convex-hull detection. The system was able to detect the distance between two points present in the hand, namely fingertip of thumb as well as index finger. Then it calculates the distance between them which is used to apply for volume and brightness, i.e. If the fingers are pinched, the distance between them becomes “zero”, thereby setting the volume or brightness to zero. If it has the maximum distance ,then the volume or brightness is set to maximum that is “100”.The Volume or brightness is decided based upon the hand. The primary aim here is to enable users to adjust the volume as well as the brightness of their system with ease, either by increasing or decreasing it. This offers a promising alternative to touch-based controls as well as voice-based controls.
Key Words: Hand Gesture, Volume Control , Brightness Control, Human Control Interaction, Edge Detection, OpenCV, Computer Vision
