Paper Info
Title
Handwritten character recognition of popular south Indian scripts
Abstract
India is a multi-lingual, multi-script country. Considerably less work has been done towards handwritten character recognition of Indian languages than for other languages. In this paper we propose a quadratic classifier based scheme for the recognition of off-line handwritten characters of three popular south Indian scripts: Kannada, Telugu, and Tamil. The features used here are mainly obtained from the directional information. For feature computation, the bounding box of a character is segmented into blocks, and the directional features are computed in each block. These blocks are then down-sampled by a Gaussian filter, and the features obtained from the down-sampled blocks are fed to a modified quadratic classifier for recognition. Here, we used two sets of features. We used 64-dimensional features for high speed recognition and 400-dimensional features for high accuracy recognition. A five-fold cross validation technique was used for result computation, and we obtained 90.34%, 90.90%, and 96.73% accuracy rates from Kannada, Telugu, and Tamil characters, respectively, from 400 dimensional features.
Year
DOI
Venue
2006
10.1007/978-3-540-78199-8_15
SACH
Keywords
Field
DocType
directional information,directional feature,high accuracy recognition,accuracy rate,popular south indian script,feature computation,handwritten character recognition,tamil character,high speed recognition,down-sampled block,indian language
Gaussian filter,Tamil,Pattern recognition,Speech recognition,Multilayer perceptron,Artificial intelligence,Engineering,Intelligent word recognition,Telugu,Quadratic classifier,Chain code,Minimum bounding box
Conference
Volume
ISSN
ISBN
4768
0302-9743
3-540-78198-6
Citations 
PageRank 
References 
12
0.68
18
Authors
4
Name
Order
Citations
PageRank
Umapada Pal11477139.32
Nabin Sharma213211.55
Tetsushi Wakabayashi336143.25
Fumitaka Kimura458467.24