Combined Hu moments, orientation knowledge, and grid intersections feature based identification of Bharatanatyam mudra images

This paper presents a three-stage methodology for identification of mudra images of Bharatanatyam dance. In the first stage, acquired images of Bharatanatyam mudras are preprocessed to obtain contours and edge images of mudras using canny edge detector. In the second stage, features such as Hu moments, mudra orientation, and grid intersections are extracted and combined feature is defined. In the third stage, a rule-based classifier is used. The proposed method is implemented using OpenCV with Microsoft visual C++ IDE. The work finds application in e-learning of ‘Bharatanatyam’ dance in particular and dances in general and automation of commentary during concerts.