Recognition of Unconstrained Handwritten Digits Using Feedforward MLP and Projection Profile

Authors

  • Rohit Kumar Singh
  • Nidhi Gulati
  • Ravi Yadav

DOI:

https://doi.org/10.37591/joces.v5i2.318

Abstract

Abstract

This paper presents a new approach to off-line handwritten numeral recognition using feedforward MLP and projection profile. Different writers have variations in their handwriting since each writer possesses own writing speed, own styles, sizes or positions for numeral or text. Recognition of handwritten numerals poses serious problems because of high variability in numeral shapes written by individuals. The performance of character recognition system depends heavily on what kind of features extraction techniques are being used. Here a handwritten numeral is scanned and this image is fed into the computer in which it is recognized using projection profile, and converted into the same word in equivalent printed characters. This paper focusses on recognition and classification of various numeral recognition techniques.

Keywords: Handwritten numeral recognition, feedforward MLP, projection profile

Cite this Article

Singh RK, Gulati N, Yadav R. Recognition of Unconstrained Handwritten Digits Using Feedforward MLP and Projection Profile. Journal of Communication Engineering & Systems. 2015; 5(2): 15–20p.

Downloads

Published

2019-04-01

Issue

Vol. 5 No. 2 (2015)

Section

Articles

License

Declaration and Copyright Transfer Form

(to be completed by authors)

I/ We, the undersigned author(s) of the submitted manuscript, hereby declare, that the above manuscript which is submitted for publication in the STM Journals(s), is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.

  • I/We will not withdraw the manuscript after 1 week of submission as I have read the Author Guidelines and will adhere to the guidelines.
  • I/We Author(s ) have niether given nor will give this manuscript elsewhere for publishing after submitting in STM Journal(s).
  • I/ We have read the original version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship.
  •  I/We also agree to the authorship of the article in the following order:

Author’s name                                    

 

1. ________________

2. ________________

3. ________________

4. ________________

 

We  Author(s) tick this box and would request you to consider it as our signature as we agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal.