NDLI: Handwritten Bangla digit recognition using Sparse Representation Classifier

Content Provider	IEEE Xplore Digital Library
Author	Khan, H.A. Al Helal, A. Ahmed, K.I.
Copyright Year	2014
Description	Author affiliation: Dept. of Electr. & Electron. Eng., United Int. Univ., Dhaka, Bangladesh (Khan, H.A.; Al Helal, A.; Ahmed, K.I.)
Abstract	We present a framework for handwritten Bangla digit recognition using Sparse Representation Classifier. The classifier assumes that a test sample can be represented as a linear combination of the train samples from its native class. Hence, a test sample can be represented using a dictionary constructed from the train samples. The most sparse linear representation of the test sample in terms of this dictionary can be efficiently computed through $ℓ_{1}-minimization,$ and can be exploited to classify the test sample. We applied Sparse Representation Classifier on the image zone density, an image domain statistical feature extracted from the character image, to classify the Bangla numerals. This is a novel approach for Bangla Optical Character Recognition, and demonstrates an excellent accuracy of 94% on the off-line handwritten Bangla numeral database CMATERdb 3.1.1. This result is promising, and should be investigated further.
Starting Page	1
Ending Page	6
File Size	1111340
Page Count	6
File Format	PDF
ISBN	9781479951796
e-ISBN	9781479951802
DOI	10.1109/ICIEV.2014.6850817
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-23
Publisher Place	Bangladesh
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Image segmentation Digit recognition Accuracy Bangla Optical Character Recognition Feature extraction Vectors Handwritten character recognition Optical character recognition software Character recognition Sparse Representation Classifier
Content Type	Text
Resource Type	Article

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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
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