NDLI: Classification of handwritten Gujarati numerals

Content Provider	IEEE Xplore Digital Library
Author	Vyas, A.N. Goswami, M.M.
Copyright Year	2015
Description	Author affiliation: Inf. Technol. Dept., Dharmsinh Desai Univ., Nadiad, India (Vyas, A.N.; Goswami, M.M.)
Abstract	This paper addresses the problem of recognizing handwritten numerals for Gujarati Language. Three methods are presented for feature extraction. One belongs to the spatial domain and other two belongs to the transform domain. In first technique, a new method has been proposed for spatial domain which is based on Freeman chain code. This method obtains the global direction by considering n × n neighbourhood and thus eliminates the noise which occurs due to local direction. In second and third method, 85 dimensional Fourier descriptors and Discrete Cosine Transform coefficients were computed and treated as feature vectors. Comparative analysis has been done for these three methods. These methods are tested with three different classifiers namely K-Nearest Neighbour, Support Vector Machine and Back Propagation Neural Network. Experimental results were evaluated using 10 fold cross validation. The highest recognition rates obtained for full data set of 3000 digits are 85.67%, 93.60% and 93.00% using modified chain code, DFT and DCT respectively.
Starting Page	1231
Ending Page	1237
File Size	286683
Page Count	7
File Format	PDF
ISBN	9781479987900
e-ISBN	9781479987924
DOI	10.1109/ICACCI.2015.7275781
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-10
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	ANN Artificial neural networks KNN SVM Modified Chain code Support vector machines Handwriting recognition Accuracy DFT DCT Feature extraction Gujarati Handwritten Numeral Recognition Discrete cosine transforms Kernel OCR
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

SVM classifier for recognition of handwritten devanagari numeral

A comparative analysis of image transformations for handwritten Odia numeral recognition

Recognition of marathi handwritten numerals by using support vector machine.

Using Modified Contour Features and SVM Based Classifier for the Recognition of Persian/Arabic Handwritten Numerals

A Supervised Time Series Feature Extraction Technique Using DCT and DWT

Handwritten Digit Recognition Using DCT and HMMs

Feature based recognition of handwritten Kannada numerals — A comparative study

Recognition of Handwritten Kannada Numerals Using Directional Features and K-Means

Classification of offline gujarati handwritten characters

Classification of handwritten Gujarati numerals

Similar Documents

SVM classifier for recognition of handwritten devanagari numeral

A comparative analysis of image transformations for handwritten Odia numeral recognition

Recognition of marathi handwritten numerals by using support vector machine.

Using Modified Contour Features and SVM Based Classifier for the Recognition of Persian/Arabic Handwritten Numerals

A Supervised Time Series Feature Extraction Technique Using DCT and DWT

Handwritten Digit Recognition Using DCT and HMMs

Feature based recognition of handwritten Kannada numerals — A comparative study

Recognition of Handwritten Kannada Numerals Using Directional Features and K-Means

Classification of offline gujarati handwritten characters

Classification of handwritten Gujarati numerals