Buddhist Hasta Mudra Recognition Using Morphological Features

Abstract

Mudras are considered as spiritual gestures in the religious sense and hold a very important place in the cultural and spiritual space in India. Images are the symbolic representations of divinity in religious artwork and their origins are conveyed through the religions and spiritual beliefs. Such gestures also have some specific meaning in the Buddhist religion. It refers to some of the events in the life of Buddha or denotes special characteristics of the Buddha deities. In recent years, automatic identification of these gestures has gained a greater interest from the machine learning community. This would help to identify the various deities that exist in the Buddhist religion, leading to digital preservation of cultural heritage art. This paper provides a framework that recognizes the Buddhist hand gesture or Hasta Mudra. The morphological features are extracted from the gesture employing geometric parameters. The experimental results show that utilising geometric features and using k-Nearest Neighbor (kNN) as a classifier, an approximately 70% recognition rate is achieved.