|本期目录/Table of Contents|

[1]付潇聪,王浩平.一种基于视觉的手势识别系统[J].电子设计工程,2017,(17):26-30.
 FU Xiao-cong,WANG Hao-ping.A vision-based hand gesture recognition system[J].SAMSON,2017,(17):26-30.
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《电子设计工程》[ISSN:1674-6236/CN:61-1477/TN]

卷:
期数:
2017年17期
页码:
26-30
栏目:
计算机技术应用
出版日期:
2017-09-05

文章信息/Info

Title:
A vision-based hand gesture recognition system
文章编号:
1674-6236(2017)17-0026-05
作者:
付潇聪王浩平
(南京理工大学 南京 江苏 210000)
Author(s):
FU Xiao-cong WANG Hao-ping
(Nanjing University of Science & Technology, Nanjing 210000,China)
关键词:
手势识别 手势分割 Hu矩 人工神经网络
Keywords:
hand gesture recognition hand segmentation Hu moment artificial neural network
分类号:
TP-9
DOI:
-
文献标志码:
A
摘要:
本文提出一种基于视觉的手势识别方法。系统由两部分组成:分割部分与识别部分。对手掌的分割:采用基于肤色的阈值分割结合YCrCb颜色空间算法,同时能够去掉人脸、多余的胳膊部分及其他噪声,得到只包含手掌的二值图。对手势的识别:采用二值图片Hu矩作为手势特征,利用BP神经网络对特征进行训练,最终实现对手指根数及一些特殊手势的识别。实验表明,该系统能有效分割手掌部分,达到对静态手势95%以上的识别率。
Abstract:
In this article, a vision-based hand gesture recognition system is proposed. The system consists of two modules: the segmentation part and the recognition part. In the segmentation part, a detection method based on skin color is used. This method is also able to segment human face, arm and other small skin-color-liked noise and keep only the palm. In the recognition part, the Hu moments are used as features of hand’s binary image. Then we apply the artificial neural network (ANN) to do the training and final recognition. A series of experiments are tested on the system, and we have more than 95% accuracy.

参考文献/References:

[1] R.Pradipa, Ms S.Kavitha. Hand gesture recognition -analysis of various techniques, methods and their algorithm[J]. International Journal of Innovation Research in Science Engineering and Technology, 2014(3):2003-2009.[2] R.Liang, M.Ouhyoung. A real-time continuous gesture recognition system for sign language [J]. Automatic Face and Gesture Recognition, 1998(3):558-567.[3] K.Grobel, M.Assan. Isolated sign language recognition using hidded Markov models [J]. Proc of the Int’1 Conf of System, Man and Cybernetics, IEEE System, Man and Cybernetics Society, 1997(5):162-167.[4] Qing Chen, Nicolas D. Georganas, Emil M. Petriu. Real-time vision-based hand gesture recognition using haar-like features[J]. Instrumentation and Measurement Technology Conference Proceedings, 2007(1):1-4.[5] S. Paul, Md. Abu Shahab Mollah, Rajibuzzaman, et al. Hand gesture recognition by artificial neural network[J]. International Conference on Mechanical, Industrial and Materials and Engineering, 2013(1):105-109.[6] Shweta K. Yewale. Artificial neural network approach for hand gesture recognition[J]. International Journal of Engineering Science and Technology, 2011,3(4):2603-2606.[7] H. Hasan, S.Abdul-Kareem. Static hand gesture recognition using neural network[J]. Artificial Intelligence, 2014(41):147-181.[8] Liu Yun,Zhang Peng. An automatic hand gesture recognition system based on viola-jones method and SVMs[J]. Second International Workshop on Computer Science and Engineering, 2009(2):72-75. [9] Hui-ShyYong Yeo, Byung-Gook Lee, Hyotaek Lim. Hand tracking and gesture recognition system for human-computer interaction using low-cost hardware[J]. Mul timed Tools Appl, 2015(74): 2687-2715.[10]Chai D, Ngan KN. Face segmentation using skin-color map in videophone applications [J]. IEEE Trans Circ Syst Video Tech, 1999,9(4):551-564.[11]Mahmoud TM. A new fast skin color detection technique[J]. Proceedings of World Academy of Science, 2008(45):501-505.[12]P.Viola,M.Jones. Robust real time face detection[J]. International Journal of Computer Vision, 2004,57(2):137-154.[13]M.K Hu. Visual pattern recognition by moment invariant[J]. IRE Transaction on Information Theory, 1962(8):179-182.[14]Y.F.Admasu, K.Raimond. Ethiopian sign language recognition using Artificial Neural Network [J]. International Conference on Intelligent Systems Design and Applications, 2011(1):995-1000.[15]T.Bouchrika,M.Zaied. Neural solutions to interact with computers by hand gesture recognition [J]. Multimedia Tools & Applications, 2013,72(3):1-27.

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备注/Memo

备注/Memo:
收稿日期:2016-09-01 稿件编号:201609010作者简介:付潇聪(1992—),男,江苏南通人,硕士。研究方向:计算机视觉。
更新日期/Last Update: 2017-09-06