Convexity Defect Based Hand Gesture Recognition Using OpenCV
AbstractThe technology of gesture recognition systems focuses on improving human-machine interaction and proximity control. This paper mainly eyes on the hand gesture recognition system that can be used for controlling different automated systems such as automated wheelchairs for physically impaired people, robotic manipulators, and similar mechanisms. Out of several techniques, a convexity defect-based system is discussed here. As the platform, Spyder is used, which is an open-source cross-platform integrated development environment (IDE). The OpenCV library is used, which is a library of functions focusing on real-time computer vision. After developing the system for multiple features of different finger-based gestures, the distance-based accuracy for each feature is measured, where at the most effective distance (2ft) the average accuracy is found to be 93.75% with real-time response. In the case of the following technique, the gesture orientation is not mattered so the system is kept simple and time-efficient. Keywords: Hand gesture recognition, convexity hull defect, human-machine interaction, Python, Spyder, OpenCV
Copyright (c) 2021 Md. Najmus Salehin, Md. Helal An Nahiyan, Fahim Islam Anik
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