Hand gesture recognition using Python and OpenCV

Abstract

Hand gesture recognition has become increasingly popular as a practical means of enhancing human-computer interaction, especially with its widespread adoption in gaming devices like Xbox and PS4, as well as in other devices such as laptops and smartphones. This technology finds applications in various fields, including accessibility support, crisis management, and medicine. Typically, these systems employ Java and a comprehensive database, showcasing various evolutionary methods and precise descriptions, along with the output and tests conducted to refine the software artifact. The proposed system is at the intersection of machine learning and image processing, utilizing different APIs and tools to streamline processes and enhance customization. It aims to be developed using OpenCV and Python, leveraging the former for image processing and the latter for machine learning. This results in a lighter system with less complex code and a reduced database footprint. This approach enables the system to run efficiently even on mini computers without compromising user experience, leading to a cost-effective solution capable of handling various tasks.