Character recognition—a review

� Abstract— Optical Character Recognition (OCR) is a very old and of great interest in pattern recognition field. In this paper we introduce a very powerful approach to recognize Persian text. We have used morphological operators, especially Hit/Miss operator to descript each sub-word and by using a template matching approach we have tried to classify generated description. We used just one font in two different sizes to verify our approach. We achieved a very good rate, up to 99.9%.

A Persian OCR System using Morphological Operators

Purpose – This paper aims to present an evaluation of open source OCR for supporting research on material in small‐ to medium‐scale historical archives.Design/methodology/approach – The approach was to develop a workflow engine to support the easy customisation of the OCR process towards the historical materials using open source technologies. Commercial OCR often fails to deliver sufficient results here, as their processing is optimised towards large‐scale commercially relevant collections. The approach presented here allows users to combine the most effective parts of different OCR tools.Findings – The authors demonstrate their application and its flexibility and present two case studies, which demonstrate how OCR can be embedded into wider digitally enabled historical research. The first case study produces high‐quality research‐oriented digitisation outputs, utilizing services that the authors developed to allow for the direct linkage of digitisation image and OCR output. The second case study demonst...

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Open source optical character recognition for historical research

This paper describes a framework for retrospective document conversion in the library domain. Drawing on the experience and insight gained from projects launched over the present decade by the European Commission, it outlines the requirements for solving the problem of retroconversion and traces the main phases of associated processing. To highlight the main problems encountered in this area, the paper also outlines studies conducted by our group in the more project for the retroconversion of old catalogues belonging to two different libraries: National French Library and Royal Belgian Library. For the French Library, the idea was to study the feasibility of a recognition approach avoiding the use of ocr and basing the strategy mainly on visual features. The challenge was to recognize a logical structure from its physical aspects. The modest results obtained from experiments for this first study led us, in the second study, to base the structural recognition methodology more on the logical aspects by focusing the analysis on the content. Furthermore, for the Belgian references, the aim was to convert reference catalogues into a more conventional unimarc format while respecting the industrial constraints. Without manual intervention, 75% rate of correct recognition was obtained on 11 catalogues containing about 4548 references.

Zinat Merali

Papers

Optical character recognition : the technology and its application in information units and libraries