Hand Sign: An Incentive-Based on Object Recognition and Detection


Authors : Vikas; Rahul Mandal

Volume/Issue : Volume 7 - 2022, Issue 5 - May

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3avweBd

The utilization of physical controllers like mouse, keyboards for HCI impedes the regular point of interaction as there is a solid boundary between the user and the PC. Hence, different strategies are assembled like speech, joint movement, and hand sign procedures to make it more natural and appealing. Over the most recent couple of years, hand gesture recognition has been viewed as an easy and normal procedure for humanmachine communication. It is one of the methods for correspondence with PCs utilizing static and dynamic development and helps us perceive messages utilizing them. Numerous applications have been developed and upgraded for hand sign recognition. These applications range from cell phones to cutting-edge advanced robotics and from gaming to clinical science. In the vast commercial and research applications, recognition of hand signs has been performed by utilizing sensor-based wired installed gloves or by utilizing vision-based methods where skin tones, chemicals, or paperclips are utilized on the hand. In any case, it is attractive to have hand sign recognition techniques that are pertinent to a natural and bare hand. Today data of various researchers and now available to experiment with Hand Sign Recognition. We have used TensorFlow, OpenCV, and Jupyter Notebook for developing the Sign Recognition System where we have trained our model for various sign languages and alphabets. We have used Object Detection Technique to build this system where our webcam takes the input data and trains the system which is working in a virtual environment. Data accuracy depends on speed. So higher the speed lowers the accuracy and vice-versa. Using different hand signs to advance continuous application we pick a Visionbased Hand Gesture Recognition System that depends on various shape features.

Keywords : Human-Computer Interaction, Data Gloves, Optical Markers, Image-Based Technologies, Vision-Based Recognition System, OpenCV, Jupyter Notebook, Tensorflow

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