Recognition of Hasta Mudra Using Star Skeleton—Preservation of Buddhist Heritage
Gopa Bhaumik, Mahesh Chandra Govil · Pattern Recognition and Image Analysis · 2021
Abstract Nonverbal communication primarily by the way of hand gestures is as old as human evolution. Before languages were developed and texts, which came much after that, hand gestures were the only way of human interaction. And hence in historical artefacts across various civilizations and religions across the world hand gestures play a predominant role, some more than others. While selecting a subject for the application of this research we wanted to zero in on a practice or religion where non-verbal communication is a prevalent part and hence our inclination towards Buddhism. In Buddhism, hand gestures (mudras) are considered as a sacred gesture that represent the different Buddha deities and their significance. The article proposes a system that identify the Buddhist hand gesture (mudras) using computer-aided technology. The system comprises a preprocessing stage, which creates a contour plot of the image to obtain the boundary of the region of interest. The features are extracted by generating a star skeleton from the preprocessed image. The star skeleton calculated by considering the local maxima of the distance signal obtained by joining the centroid with the boundary pixels describes the mudras. Each of these mudras has a different star skeleton. The star skeletons computed from the known sample images are used to build a database for the recognition system. The recognition is achieved by choosing the template with the most similar skeleton retrieved from the database.