DocumentCode :
3527668
Title :
Handwritten Character Recognition Using Wavelet Transform and Hopfield Network
Author :
Malik, Pravanjan ; Dixit, Rahul
Author_Institution :
Dept. of Comput. Sci. & Eng., MRCE, Faridabad, India
fYear :
2013
fDate :
21-23 Dec. 2013
Firstpage :
125
Lastpage :
129
Abstract :
An off-line handwritten alphabetical character recognition system using Wavelet Transform and Hop field Network is described in the paper. Hop field Network has been used in the system as they are known for their ability to retain patterns. The wavelet transforms are used for extracting features from the images. The results show that the network was able to recognize all the characters at a distortion level of 30%, at 40% it recognized only a few characters and at all the distortion levels above 40% it was not able to recognize any of the characters.
Keywords :
Hopfield neural nets; feature extraction; handwritten character recognition; wavelet transforms; Hopfield network; feature extraction; handwritten character recognition; off-line handwritten alphabetical character recognition system; wavelet transform; Character recognition; Discrete wavelet transforms; Feature extraction; Hopfield neural networks; Vectors; Handwritten Character Recognition; Hopfield Network; Wavelet Transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Intelligence and Research Advancement (ICMIRA), 2013 International Conference on
Conference_Location :
Katra
Type :
conf
DOI :
10.1109/ICMIRA.2013.31
Filename :
6918808
Link To Document :
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