NDLI: A benchmark image database of isolated Bangla handwritten compound characters

Content Provider	Springer Nature Link
Author	Das, Nibaran Acharya, Kallol Sarkar, Ram Basu, Subhadip Kundu, Mahantapas Nasipuri, Mita
Copyright Year	2014
Abstract	In the present work, we present a benchmark image database of isolated handwritten Bangla compound characters, used in the standard Bangla literature. A thorough survey over more than 2 million Bangla words has revealed that there exist around 334 compound characters in Bangla script. Of which, only around 171 character classes form unique pattern shapes, and some of these classes are often written in multiple styles. Altogether, 55,278 isolated character images, belonging to 199 different pattern shapes, are collected using three different data collection modalities. The database is divided into training and test sets in 4:1 ratio for each pattern class, by considering a balanced distribution of shapes from different modalities. A convex hull and quadtree-based feature set has been designed, and the test set recognition performance is reported with the support vector machine classifier. We have achieved a recognition accuracy of 79.35 % on the test database consisting of 171 character classes. The complete compound character image database is freely available as CMATERdb 3.1.3.3 from the website http://code.google.com/p/cmaterdb/ , which may facilitate research on handwritten character recognition, especially related to Bangla form document processing systems.
Starting Page	413
Ending Page	431
Page Count	19
File Format	PDF
ISSN	14332833
Journal	International Journal of Document Analysis and Recognition (IJDAR)
Volume Number	17
Issue Number	4
e-ISSN	14332825
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2014-05-23
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	OCR Handwritten character recognition Bangla Compound character Benchmark database SVM Image Processing and Computer Vision Pattern Recognition
Content Type	Text
Resource Type	Article
Subject	Computer Science Applications Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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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