The Recognition of Handwritten Numbers by Extracting New Features Using Water Filling Method

Author

Enayatifar, Rasul ; Sadeghi, Hossein ; Mirzaei, Khadije

Author_Institution

Firoozkuh Branch, Azad Univ., Firoozkuh, Iran

fYear

2009

fDate

7-9 March 2009

Firstpage

51

Lastpage

56

Abstract

In this paper, a new method is proposed to extract the features of a one-number Persian image in which for the final verification of the extracted features, a three-layer neural network (mesh) of Perceptron has been utilized. The method, which is called Water Filling method, is capable of extracting some ideal features from a one-number image that are stable against rotation, movement, size change and noise. The method is examined on a database of 60000 discretized numbers, from which 40000 numbers were used in the training stage and 20000 ones were used for the experiment. The recognition percentage of 92.7% shows the great efficiency of the proposed method.

Keywords

feature extraction; handwritten character recognition; multilayer perceptrons; feature extraction; final verification; handwritten numbers recognition; neural network; one-number Persian image; perceptron; water filling method; Electronic mail; Feature extraction; Filling; Handwriting recognition; Image databases; Image recognition; Multi-layer neural network; Neural networks; Spatial databases; Water resources; Features Extraction; Perceptron Neural Network; Recognition of Persian Numbers; Water Filling Method;

fLanguage

English

Publisher

ieee

Conference_Titel

Future Networks, 2009 International Conference on

Conference_Location

Bangkok

Print_ISBN

978-0-7695-3567-8

Type

conf

DOI

10.1109/ICFN.2009.26

Filename

5189897