Devanagari handwritten numeral identification based on Zernike moments

Author

More, V.N. ; Rege, P.P.

Author_Institution

Electron. & Telecommun. Dept., Coll. of Eng. Pune, Pune

fYear

2008

fDate

19-21 Nov. 2008

Firstpage

1

Lastpage

6

Abstract

The preprocessing of numerals includes bounding them for translation invariance followed by normalization for scale invariance. We achieve translation and scale invariance using simple geometric moments. Higher order Zernike moments are used as shape descriptors. Due to rotation invariance and orthogonal properties of Zernike moments, they are found to perform better in terms of computational complexity and classification achieved. The algorithm has been tested on different handwritten samples taken from different people. In this paper, an attempt is made to develop off-line recognition system for isolated Devanagari numerals.

Keywords

computational complexity; geometry; handwritten character recognition; Devanagari handwritten numeral identification; computational complexity; geometric moments; higher order Zernike moments; numeral preprocessing; off-line recognition system; orthogonal properties; rotation invariance; scale invariance; shape descriptors; translation invariance; Character recognition; Computational complexity; Educational institutions; Feature extraction; Fuzzy logic; Handwriting recognition; Neural networks; Shape; Testing; Writing; Devanagari script; Geometric moments; Zernike moments; rotation invariance;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON 2008 - 2008 IEEE Region 10 Conference

Conference_Location

Hyderabad

Print_ISBN

978-1-4244-2408-5

Electronic_ISBN

978-1-4244-2409-2

Type

conf

DOI

10.1109/TENCON.2008.4766863

Filename

4766863