iTextMM: Intelligent Text Input System for Myanmar Language on Android Smartphone

Author(s):  
Nandar Pwint Oo ◽  
Ni Lar Thein
Keyword(s):  
Author(s):  
Kumiko Tanaka-Ishii ◽  
Yusuke Inutsuka ◽  
Masato Takeichi

1980 ◽  
Author(s):  
K. Shirai ◽  
Y. Fukazawa ◽  
T. Matzui ◽  
H. Matzuura

2009 ◽  
Vol 9 (12) ◽  
pp. 94-102
Author(s):  
Sung-Jun Park ◽  
Ji-Won Lee ◽  
Hee-Dong Chang

2017 ◽  
Vol 101 (2) ◽  
pp. 9-22 ◽  
Author(s):  
HIRONOBU SATO ◽  
KIYOHIKO ABE ◽  
SHOICHI OHI ◽  
MINORU OHYAMA

2013 ◽  
Vol 401-403 ◽  
pp. 1377-1380 ◽  
Author(s):  
Kun Wei Chen ◽  
Xing Guo ◽  
Jian Guo Wu

Vision-based gesturerecognition is a key technique to achieve a new generation of human-computerinteraction. As few text input search system by gesture recognition isdeveloped, based on the existing gesture recognition techniques, we use thegestures which are corresponding to the Chinese letters and numbers as inputgesture and use Microsoft kinect to obtain depth image to conduct hand gesturesegmentation. First, the edge of the gesture is extracted by Canny algorithm,and then the feature is extracted based on wavelet moment. Finally the gestureletters are obtained. Achieved the text input system based on gesturerecognition. Experiments show that the system is able to achieve Chinesecharacters accurately and effectively.


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