most citedHandwritten Bangla Basic and Compound character recognition using MLP and SVM classifier

81 citations · 244 across the 13 of their papers we have counts for

collaborators

13 papers

cs.GR201017 cited

Text/Graphics Separation for Business Card Images for Mobile Devices

Ayatullah Faruk Mollah, Subhadip Basu, Mita Nasipuri +1

Separation of the text regions from background texture and graphics is an important step of any optical character recognition sytem for the images containg both texts and graphics.…

cs.CV201012 cited

Recognition of handwritten Roman Numerals using Tesseract open source OCR engine

Sandip Rakshit, Amitava Kundu, Mrinmoy Maity +3

The objective of the paper is to recognize handwritten samples of Roman numerals using Tesseract open source Optical Character Recognition (OCR) engine. Tesseract is trained with d…

cs.CV20105 cited

Development of a Multi-User Recognition Engine for Handwritten Bangla Basic Characters and Digits

Sandip Rakshit, Debkumar Ghosal, Tanmoy Das +2

The objective of the paper is to recognize handwritten samples of basic Bangla characters using Tesseract open source Optical Character Recognition (OCR) engine under Apache Licens…

cs.CV201026 cited

Recognition of Handwritten Textual Annotations using Tesseract Open Source OCR Engine for information Just In Time (iJIT)

Sandip Rakshit, Subhadip Basu, Hisashi Ikeda

Objective of the current work is to develop an Optical Character Recognition (OCR) engine for information Just In Time (iJIT) system that can be used for recognition of handwritten…

cs.CV20104 cited

Recognition of Handwritten Roman Script Using Tesseract Open source OCR Engine

Sandip Rakshit, Subhadip Basu

In the present work, we have used Tesseract 2.01 open source Optical Character Recognition (OCR) Engine under Apache License 2.0 for recognition of handwriting samples of lower cas…

cs.CV20104 cited

Development of a multi-user handwriting recognition system using Tesseract open source OCR engine

Sandip Rakshit, Subhadip Basu

The objective of the paper is to recognize handwritten samples of lower case Roman script using Tesseract open source Optical Character Recognition (OCR) engine under Apache Licens…