Hand Gesture Recognition of English Alphabets using Artificial Neural Network

被引:0
作者
Bhowmick, Sourav [1 ]
Kumar, Sushant [1 ]
Kumar, Anurag [1 ]
机构
[1] Tezpur Univ, Sch Engn, Tezpur 785024, Assam, India
来源
2015 IEEE 2ND INTERNATIONAL CONFERENCE ON RECENT TRENDS IN INFORMATION SYSTEMS (RETIS) | 2015年
关键词
Human computer interaction; Hand gesture recognition; Hand segmentation; Movement epenthesis; Multilayer perceptron; Focused time delay neural network;
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
Human computer interaction (HCI) and sign language recognition (SLR), aimed at creating a virtual reality, 3D gaming environment, helping the deaf-and-mute people etc., extensively exploit the use of hand gestures. Segmentation of the hand part from the other body parts and background is the primary need of any hand gesture based application system; but gesture recognition systems are often plagued by different segmentation problems, and by the ones like co-articulation, movement epenthesis, recognition of similar gestures etc. The principal objective of this paper is to address a few of the said problems. In this paper, we propose a method for recognizing isolated as well as continuous English alphabet gestures which is a step towards helping and educating the hearing and speech-impaired people. We have performed the classification of the gestures with artificial neural network. Recognition rate (RR) of the isolated gestures is found to be 92.50% while that of continuous gestures is 89.05% with multilayer perceptron and 87.14% with focused time delay neural network. These results, when compared with other such system in the literature, go into showing the effectiveness of the system.
引用
收藏
页码:405 / 410
页数:6
相关论文
共 13 条
[1]  
Al-Ahdal M. Ebrahim, 2012, 2012 IEEE Symposium on Computers & Informatics, P52, DOI 10.1109/ISCI.2012.6222666
[2]  
[Anonymous], 2008, LEARNING OPENCV COMP
[3]   A novel set of features for continuous hand gesture recognition [J].
Bhuyan, M. K. ;
Kumar, D. Ajay ;
MacDorman, Karl F. ;
Iwahori, Yuji .
JOURNAL ON MULTIMODAL USER INTERFACES, 2014, 8 (04) :333-343
[4]  
Bhuyan MK., 2008, WORLD ACAD SCI ENG T, V21, P753
[5]  
Duda R.O., 2009, Pattern Classification, V2nd
[6]  
Elmezain M, 2008, JOURNAL WSCG, V16, P65
[7]  
Liu N, 2003, PROCEEDINGS OF THE 3RD IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY, P648
[8]  
Liu NJ, 2004, NINTH INTERNATIONAL WORKSHOP ON FRONTIERS IN HANDWRITING RECOGNITION, PROCEEDINGS, P100
[9]  
Mazumdar D., 2013, INT J ELECT SIGNALS, V3, P71
[10]   Gesture recognition: A survey [J].
Mitra, Sushmita ;
Acharya, Tinku .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS, 2007, 37 (03) :311-324