Contour-Based Real-Time Hand Gesture Recognition for Indian Sign Language

被引：4

作者：

Itkarkar, Rajeshri R. ^{[1
]}

Nandi, Anilkumar ^{[1
]}

Mane, Bhagyashri ^{[2
]}

机构：

[1] BVB COE, Hubli, India

[2] JSPMs RSCOE, Pune, Maharashtra, India

来源：

COMPUTATIONAL INTELLIGENCE IN DATA MINING, CIDM 2016 | 2017年 / 556卷

关键词：

Gesture recognition; Hand gestures; Harris corner detector;

D O I：

10.1007/978-981-10-3874-7_65

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Gesture recognition system is widely being developed recently as gesture-controlled devices are on a large scale used by the consumers. The gesture may be in static or in dynamic form, typically applied in robot control, gaming control, sign language recognition, television control etc. This paper focuses on the use of dynamic gestures for Indian sign language recognition. The methodology is implemented in real time for hand gestures using contour and convex hull for feature extraction and Harris corner detector for gesture recognition. The accuracy results are obtained under strong, dark, and normal illumination. The overall accuracy achieved for Indian sign language recognition under dark illumination is 81.66. With Indian sign language application, the recognized gesture can also be applied for any machine interaction.

引用

页码：683 / 691

页数：9

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