DocumentCode
2015247
Title
A Feature based on Encoding the Relative Position of a Point in the Character for Online Handwritten Character Recognition
Author
Dinesh, M. ; Sridhar, Murali Krishna
Author_Institution
HP Lab., Bangalore
Volume
2
fYear
2007
fDate
23-26 Sept. 2007
Firstpage
1014
Lastpage
1017
Abstract
Feature extraction is a very important step in the process of character recognition. The features extracted from the character should encode the local, global and the structural characteristics of the character shape. In this paper we propose a new feature for recognition of online handwritten characters called the star feature. The star feature encodes the local, global and structural characteristics of a character. The star feature describes every point of the character, in terms of its relative position with respect to the other points in the character. We have evaluated the performance of the star feature on IRONOFF data set and IWFHR-06 Tamil competition data set. The experimental results show that the star feature achieves high accuracy on both the data sets.
Keywords
feature extraction; handwritten character recognition; pattern classification; IRONOFF data set; IWFHR-06 Tamil competition data set; character shape; feature extraction; online handwritten character recognition; star feature; Character recognition; Data mining; Encoding; Feature extraction; Handwriting recognition; Shape; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition, 2007. ICDAR 2007. Ninth International Conference on
Conference_Location
Parana
ISSN
1520-5363
Print_ISBN
978-0-7695-2822-9
Type
conf
DOI
10.1109/ICDAR.2007.4377068
Filename
4377068
Link To Document