Recognition of Handwritten Roman Script Using Tesseract Open source OCR Engine

03/30/2010
by   Sandip Rakshit, et al.
0

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 case Roman script. Handwritten isolated and free-flow text samples were collected from multiple users. Tesseract is trained to recognize user-specific handwriting samples of both the categories of document pages. On a single user model, the system is trained with 1844 isolated handwritten characters and the performance is tested on 1133 characters, taken form the test set. The overall character-level accuracy of the system is observed as 83.5 and erroneously classifies 10.94

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/30/2010

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

The objective of the paper is to recognize handwritten samples of lower ...
research
12/02/2016

Recognition of Text Image Using Multilayer Perceptron

The biggest challenge in the field of image processing is to recognize d...
research
03/30/2010

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

The objective of the paper is to recognize handwritten samples of basic ...
research
03/30/2010

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

Objective of the current work is to develop an Optical Character Recogni...
research
07/04/2019

A Novel Approach to OCR using Image Recognition based Classification for Ancient Tamil Inscriptions in Temples

Recognition of ancient Tamil characters has always been a challenge for ...
research
03/11/2021

Full Page Handwriting Recognition via Image to Sequence Extraction

We present a Neural Network based Handwritten Text Recognition (HTR) mod...
research
01/19/2022

Open Source Handwritten Text Recognition on Medieval Manuscripts using Mixed Models and Document-Specific Finetuning

This paper deals with the task of practical and open source Handwritten ...

Please sign up or login with your details

Forgot password? Click here to reset