International Journal of Computer Science & Engineering Technology

ISSN : 2229-3345

Open Access
Open Access

ABSTRACT

Title : A Novel Technique for Image Compression in Hand Written Recognition using Back Propagation in Neural Network
Authors : P.Padmasree, Maheswari.R
Keywords : Handwritten symbol recognition, Neural Networks, Back-propagation.
Issue Date : June 2013
Abstract :
The handwritten symbol recognition plays an important role in present communication systems. In the data communication systems, all the data have to be recorded, encoded and will be communicated with other systems. Presently this communication system extracts the digital and non-digital information from printers, scanners, and touch screens and from the image processing techniques which will be fed into the different pattern recognition algorithms. The digital data communication is easier rather than non-digital data communication like hand written symbols due to the variation of styles, size and shapes of the handwritten symbols from person to person so we have to compress the image which helps to reduce the storage space and the transmission cost . This paper presents implementation of handwritten symbol recognition using back-propagation algorithm in neural networks using MATLAB with training dataset which will give the compressed image exactly with improved resolution. This algorithm helps to increase the performance of the system.
Page(s) : 763-768
ISSN : 2229-3345
Source : Vol. 4, Issue.6

Copyright © 2010-2024 IJCSET KEJA Publications