A Statistical Approach to Efficient Curvature Scale Space Matching for Recognizing Hand Gestures

被引：0
|
作者：
Sarkar, Soumajyoti [1 ]
Pal, Avik [1 ]
Sil, Jaya [1 ]
机构：
[1] Indian Inst Engn Sci & Technol, Dept Comp Sci & Technol, Howrah, W Bengal, India
来源：
2014 9TH INTERNATIONAL CONFERENCE ON INDUSTRIAL AND INFORMATION SYSTEMS (ICIIS) | 2014年
关键词：
curvature scale space; hand gestures; curve matching; shape matching; image segmentation;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In the paper, we develop an efficient matching algorithm for recognizing different types of hand gestures. The algorithm has been performed on an input image window in three stages: first the skin regions are segmented using a global threshold technique. Then a curvature scale space (CSS) image is created considering the largest contour of the segmented skin regions. Finally, a novel approach using statistical measure has been applied to match the input CSS image and the set of previously stored model CSS images. The algorithm is robust since it uses global distribution of the CSS image as part of the matching algorithm and performs better than the previous methods applied for shape similarity using curvature scale space (CSS) matching.
引用
收藏
页码：188 / 193
页数：6
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