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

机译:结合胡矩,取向知识和网格交点特征的Bharatanatyam手印图像识别

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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.
机译:本文提出了一种三阶段的方法来识别婆罗多摩舞的手印图像。在第一阶段,使用Canny边缘检测器对获取的Bharatanatyam粘液图像进行预处理,以获得轮廓和边缘图像。在第二阶段中,提取诸如Hu矩,手印方向和网格交点之类的特征,并定义组合特征。在第三阶段,使用基于规则的分类器。所提出的方法是使用带有Microsoft Visual C ++ IDE的OpenCV来实现的。该作品可用于特别是“ Bharatanatyam”舞蹈的电子学习,尤其适用于一般舞蹈和音乐会期间评论的自动化。

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