DocumentCode
3412624
Title
A real time numeric character recognition system using artificial neural network
Author
Farhad, M.M. ; Nafiul Hossain, S.M. ; Hossain, Md Imtiaz ; Mishu, Ripon Shaha ; Hossain, Shamim Shahriar ; Alam Khan, Md Fakhrul
fYear
2013
fDate
19-21 Dec. 2013
Firstpage
363
Lastpage
367
Abstract
In a Human Computer Interaction System the recognition of any handwritten character plays an important role. The recognition of numeric character is thus a matter of concern in order to operate a computer in a real time environment. In this paper a method of numeric character recognition is proposed where the fingertip movement is used for the recognition of handwritten character recognition. Our finger tip changes its direction during the writing of numeric characters. This variation in angular movements is used to construct the dataset for the recognition system. This angular variation is used as the input of Multilayer Neural Network training and its validity was tested for a number of objects. Experimental result shows that the proposed algorithm shows better result for the real time applications.
Keywords
handwritten character recognition; human computer interaction; learning (artificial intelligence); neural nets; angular movements; angular variation; artificial neural network; fingertip movement; handwritten character recognition; human computer interaction system; multilayer neural network training; real time environment; real time numeric character recognition system; Artificial neural networks; Character recognition; Handwriting recognition; Real-time systems; Thumb; Artificial Neural Network; Blob detection; Finger tip detection; Reference axis;
fLanguage
English
Publisher
ieee
Conference_Titel
Advances in Electrical Engineering (ICAEE), 2013 International Conference on
Conference_Location
Dhaka
Print_ISBN
978-1-4799-2463-9
Type
conf
DOI
10.1109/ICAEE.2013.6750364
Filename
6750364
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