Robust Multifont OCR System from Gray Level Images

Authors:
Frank LeBourgeois
Affiliations:
-
Venue:
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Year:
1997

Citing 0
Cited 4

A High Accuracy Rate Commercial Flight Coupon Recognition System

ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Recognition of Container Code Characters through Gray-Level Feature Extraction and Gradient-Based Classifier Optimization

ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Development of a Guide Dog System for the Blind with Character Recognition Ability

CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Text line segmentation for gray scale historical document images

Proceedings of the 2011 Workshop on Historical Document Imaging and Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a general robust OCR system designed for practical use and suited to unconstrained gray-level images grabbed from a CCD camera. The system works with minimum assumptions on font , text location, size, color and the background scene. To avoid the threshold problems with text segmentation and feature extraction, which depend on character binarization, we propose to process the full gray level image directly. The text blocks localization in complex scenes using a specific filter which enhances any text from the backgound without binarization. A special stage is designed to separate characters, even touched, by using gray-level information. We also extract gray-level features which make the algorithm more reliable, in particular under poor printing conditions or bad contrast digitization.