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

Combined Hu moments, orientation knowledge, and grid intersections feature based identification... 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. Keywords Contour of mudras · Hu moments · Lines in mudra · Orientation of mudra · Height_Width_Difference · Rule- based classifier 1 Introduction of some of Bharatanatyam dance along with some mudras. A mudra is the most striking feature of this Indian classical The research in digital image processing, particularly in the last dance, which uses hand gestures. Hand sign is a ritual gesture few decades, has led to many recent developments of image in Hinduism and Buddhism. Speaking in dance via gestures processing applications. One such significant application is is a way of nonverbal communication, rather than orally, in seen in Bharatanatyam dance http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Pattern Analysis and Applications Springer Journals

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

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Publisher
Springer London
Copyright
Copyright © 2018 by Springer-Verlag London Ltd., part of Springer Nature
Subject
Computer Science; Pattern Recognition
ISSN
1433-7541
eISSN
1433-755X
D.O.I.
10.1007/s10044-018-0715-2
Publisher site
See Article on Publisher Site

Abstract

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. Keywords Contour of mudras · Hu moments · Lines in mudra · Orientation of mudra · Height_Width_Difference · Rule- based classifier 1 Introduction of some of Bharatanatyam dance along with some mudras. A mudra is the most striking feature of this Indian classical The research in digital image processing, particularly in the last dance, which uses hand gestures. Hand sign is a ritual gesture few decades, has led to many recent developments of image in Hinduism and Buddhism. Speaking in dance via gestures processing applications. One such significant application is is a way of nonverbal communication, rather than orally, in seen in Bharatanatyam dance

Journal

Pattern Analysis and ApplicationsSpringer Journals

Published: Jun 2, 2018

References

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