NDLI: A System for Off-Line Oriya Handwritten Character Recognition Using Curvature Feature

Content Provider	IEEE Xplore Digital Library
Author	Pal, U. Wakabayashi, T. Kimura, F.
Copyright Year	2007
Description	Author affiliation: Indian Stat. Inst., Kolkata (Pal, U.)
Abstract	In this paper we present a system towards the recognition of off-line Oriya handwritten characters. Since most of the Oriya characters have curve-like stroke, we use curvature feature for the recognition purpose. To get the feature, at first, the input image is size normalized and segmented into 49times49 blocks. Curvature is then computed using bi-quadratic interpolation method and quantized into 3 levels according to concave, linear and convex regions. Next direction of gradient is quantized into 32 levels with pi/16 intervals, and strength of the gradient is accumulated in each of the 32 directions and in each of the 3 curvature levels of every block. A spatial resolution is made to get 7times7 blocks from 49times49 blocks and a directional resolution is made to get 8 directions from 32 directions. Using curvature features for 3 levels we get 1176 (7times7 blocks times 8 directions times 3 levels) dimensional features. Finally using principal component analysis we reduce the dimension 1176 to 392 and this 392 dimensional feature vector is fed to a quadratic classifier for recognition. We tested 18190 samples of Oriya handwritten samples and obtained 94.60% accuracy from our proposed system.
Starting Page	227
Ending Page	229
File Size	354756
Page Count	3
File Format	PDF
ISBN	0769530680
DOI	10.1109/ICIT.2007.63
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-17
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Handwriting recognition Computer vision Image segmentation Interpolation Shape Speech recognition Pattern recognition Character recognition Spatial resolution Information technology
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A new scheme for off-line handwritten connected digit recognition

Off-Line Handwritten Character Recognition of Devnagari Script

Hidden Markov random field based approach for off-line handwritten Chinese character recognition

Off-line handwritten Arabic character segmentation algorithm: ACSA

Handwriting segmentation of unconstrained Oriya text

Shape detection using gradient features for handwritten character recognition

Using lexical similarity in handwritten word recognition

A Baseline Dependent Approach for Persian Handwritten Character Segmentation

An efficient handwritten Devnagari character recognition system using neural network

A System for Off-Line Oriya Handwritten Character Recognition Using Curvature Feature

Similar Documents

A new scheme for off-line handwritten connected digit recognition

Off-Line Handwritten Character Recognition of Devnagari Script

Hidden Markov random field based approach for off-line handwritten Chinese character recognition

Off-line handwritten Arabic character segmentation algorithm: ACSA

Handwriting segmentation of unconstrained Oriya text

Shape detection using gradient features for handwritten character recognition

Using lexical similarity in handwritten word recognition

A Baseline Dependent Approach for Persian Handwritten Character Segmentation

An efficient handwritten Devnagari character recognition system using neural network

A System for Off-Line Oriya Handwritten Character Recognition Using Curvature Feature