IJDAR (2012) 15:71–83 DOI 10.1007/s10032-011-0148-6 ORIGINAL PAPER CMATERdb1: a database of unconstrained handwritten Bangla and Bangla–English mixed script document image Ram Sarkar · Nibaran Das · Subhadip Basu · Mahantapas Kundu · Mita Nasipuri · Dipak Kumar Basu Received: 3 June 2010 / Revised: 18 August 2010 / Accepted: 24 January 2011 / Published online: 24 February 2011 © Springer-Verlag 2011 Abstract In this paper, we have described the preparation of a benchmark database for research on off-line Optical Character Recognition (OCR) of document images of hand- written Bangla text and Bangla text mixed with English words. This is the first handwritten database in this area, as mentioned above, available as an open source document. As India is a multi-lingual country and has a colonial past, so multi-script document pages are very much common. The database contains 150 handwritten document pages, among which 100 pages are written purely in Bangla script and rests of the 50 pages are written in Bangla text mixed with Eng- lish words. This database for off-line-handwritten scripts is collected from different data sources. After collecting the document pages, all the documents have been preprocessed and distributed into two groups, i.e., CMATERdb1.1.1, con- Electronic supplementary material The online version of this article (doi:10.1007/s10032-011-0148-6) contains supplementary material, which is available to authorized users. R. Sarkar · N. Das · S. Basu · M. Kundu · M. Nasipuri (B ) Computer Science and Engineering Department, Jadavpur University, Kolkata 700032, India e-mail: nasipuri@vsnl.com R. Sarkar e-mail: raamsarkar@gmail.com N. Das e-mail: nibaran@gmail.com S. Basu e-mail: subhadip8@yahoo.com M. Kundu e-mail: mkundu@cse.jdvu.ac.in D. K. Basu A.I.C.T.E. Emeritus Fellow, Computer Science and Engineering Department, Jadavpur University, Kolkata 700032, India e-mail: dipakkbasu@gmail.com taining document pages written in Bangla script only, and CMATERdb1.2.1, containing document pages written in Bangla text mixed with English words. Finally, we have also provided the useful ground truth images for the line seg- mentation purpose. To generate the ground truth images, we have first labeled each line in a document page automatically by applying one of our previously developed line extraction techniques [Khandelwal et al., PReMI 2009, pp. 369–374] and then corrected any possible error by using our developed tool GT Gen 1.1. Line extraction accuracies of 90.6 and 92.38% are achieved on the two databases, respectively, using our algorithm. Both the databases along with the ground truth annotations and the ground truth generating tool are available freely at http://code.google.com/p/cmaterdb. Keywords Unconstrained handwritten document image database · Text line extraction · Ground truth preparation · OCR of multi-script document 1 Introduction OCR involves computer recognition of characters from dig- itized images of optically scanned document pages. The characters thus recognized from document pages are coded with American Standard Code for Information Interchange (ASCII) or some other standard code for storing in a file, which can be edited as any other file created with some word processing software or some editor. A scanner with OCR facility allows editing the contents of document pages after scanning them optically. Identification of text lines is the first and most important step in the process of OCR of handwritten/printed document images. If text line identification is not accurate, then none of the words and characters in the constituent text lines can be 123