NDLI: Devnagari Handwritten Character Recognition using LBG vector quantization with gradient masks

Content Provider	IEEE Xplore Digital Library
Author	Kekre, H.B. Thepade, S.D. Sanas, S.P. Shinde, S.
Copyright Year	2013
Description	Author affiliation: R.A.I.T., Mumbai, India (Shinde, S.) \|\| PVPPCOE, Mumbai, India (Sanas, S.P.) \|\| Dept. of Comput. Eng., Pimpri Chinchwad Coll. of Eng., Pune, India (Thepade, S.D.) \|\| Mukesh Patel Sch. of Technol. Manage. & Eng., Dept. of Comput. Eng., SVKM's NMIMS, Mumbai, India (Kekre, H.B.)
Abstract	Several ways to generalize the Devanagari handwritten character recognition have been proposed in the past. In this paper, novel method of Handwritten Character Recognition with Shape and Texture features has been proposed. The method proposed here does not need the Preprocessing and Character Tokenization. The Shape features and Texture feature are more unique, so a novel technique based on combination of these is derived and proposed here. For extracting shape features standard gradient operator such as Robert, Prewitt, Sobel, Canny and Laplace are used and for texture feature vector quantization technique. The gradient mask images of the character images are obtained and then LBG vector quantization algorithm is applied on these gradient images to get the codebooks of various sizes. These obtained LBG codebooks are considered as shape texture feature vectors for handwritten character recognition. In all 40 variations of the character recognition method are proposed using five gradient operators and 9 code book sizes (from 4 to 1024). For experimentation the database having 72 images from 6 samples per character with 12 different characters is used. The crossover point of precision and recall is considered as performance comparison criteria for proposed character recognition techniques. The best performance is observed in LBG for codebook size 8 of Sobel operator and the next best is seen for codebook sizes 8 and 16 of Prewitt and Laplace gradient mask for feature extraction.
Sponsorship	IEEE Bombay Sect.
Starting Page	1
Ending Page	4
File Size	175411
Page Count	4
File Format	PDF
ISBN	9781467356183
e-ISBN	9781467356190
DOI	10.1109/ICAdTE.2013.6524768
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-23
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Image edge detection Vector quantization Canny Sobel Vectors Character recognition Optical character recognition software Prewitt and Laplace KEVR Robert CBIR Feature extraction VQ
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

CBIR using KEVR vector quantization applied on gradient mask edge images

Recognition of American sign language using LBG vector quantization

Lbg vector quantization for recognition of handwritten marathi barakhadi.

Shape Extraction Using Edge Detection Techniques

Feature extraction from epigenetic traits using edge detection in iris recognition system

Comparison of edge detectors

A Comparison of various Edge Detection Techniques used in Image Processing

Edge Detection with a Preprocessing Approach

COMPARATIVE STUDY OF EDGE DETECTION TECHNIQUES FOR STEGANOGRAPHY.

Devnagari Handwritten Character Recognition using LBG vector quantization with gradient masks

Similar Documents

CBIR using KEVR vector quantization applied on gradient mask edge images

Recognition of American sign language using LBG vector quantization

Lbg vector quantization for recognition of handwritten marathi barakhadi.

Shape Extraction Using Edge Detection Techniques

Feature extraction from epigenetic traits using edge detection in iris recognition system

Comparison of edge detectors

A Comparison of various Edge Detection Techniques used in Image Processing

Edge Detection with a Preprocessing Approach

COMPARATIVE STUDY OF EDGE DETECTION TECHNIQUES FOR STEGANOGRAPHY.

Devnagari Handwritten Character Recognition using LBG vector quantization with gradient masks