Persian sign language (PSL) recognition using wavelet transform and neural networks

被引:71
作者
Karami, Ali [1 ]
Zanj, Bahman [1 ]
Sarkaleh, Azadeh Kiani [1 ]
机构
[1] Univ Guilan, Fac Engn, Rasht, Iran
关键词
Persian sign language; Hand gesture; Discrete wavelet transform (DWT); Neural network (NN); ASL RECOGNITION;
D O I
10.1016/j.eswa.2010.08.056
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a system for recognizing static gestures of alphabets in Persian sign language (PSL) using Wavelet transform and neural networks (NN). The required images for the selected alphabets are obtained using a digital camera. The color images are cropped, resized, and converted to grayscale images. Then, the discrete wavelet transform (DWT) is applied on the gray scale images, and some features are extracted. Finally, the extracted features are used to train a Multi-Layered Perceptron (MLP) NN. Our recognition system does not use any gloves or visual marking systems. This system only requires the images of the bare hand for the recognition. The system is implemented and tested using a data set of 640 samples of Persian sign images; 20 images for each sign. Experimental results show that our system is able to recognize 32 selected PSL alphabets with an average classification accuracy of 94.06%. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2661 / 2667
页数:7
相关论文
共 31 条
[1]  
[Anonymous], P INT REAL VIRT WORL
[2]  
[Anonymous], 2006, Digital Image Processing
[3]  
Bahadori I., 1992, PERSIAN SIGN LANGUAG
[4]  
CHEN Y, 2003, P IEEE INT WORKSH AN
[5]  
Demuth H., 2006, NEURAL NETWORK TOOLB
[6]  
DINH TB, 2006, 2006 INT C RES INN V, P139
[7]  
Fausett L., 1994, Fundamentals of neural networks: architectures, algorithms, and applications
[8]  
Grobel K, 1997, IEEE SYS MAN CYBERN, P162, DOI 10.1109/ICSMC.1997.625742
[9]  
Heykin S, 1999, NEURAL NETWORKS COMP
[10]  
HOLDEN EJ, 1999, P INT C SIGN IM PROC, P141