Machine learning approach to the classification and identification of hand gesture recognition using python

Research Article
Dr. Anjaneya L H., Dr.Mahanthesha U and Banumathi K L
DOI: 
http://dx.doi.org/10.24327/ijrsr.20231411.0821
Subject: 
Electrical and Electronics Engineering
KeyWords: 
Gesture recognition, OpenCV, human-computer interaction, python, machine learning
Abstract: 

People who are deaf or dumb express themselves through gestures. Numerous applications utilizing gesture detection, computer vision, machine learning, etc. have been created. Python-based hand gesture recognition is an interesting area of computer vision that seeks to read and comprehend hand motions and movements recorded by cameras. It is utilized in a variety of fields, including robotics, virtual reality, sign language interpretation, and human computer interface. The classification and interpretation of hand gestures is the aim of hand gesture recognition. In this paper, a straightforward method for gesture recognition is provided. Opencv and Numpy are two Python libraries used here. The method entails capturing real-time gestures and utilizing OpenCV tools to recognize them. The screen for output displays the output as a computer webcam stream.