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Word-Based adaptive OCR for historical books

Kluzner, V, Tzadok, A, Shimony, Y, Walach, E and Antonacopoulos, A 2009, Word-Based adaptive OCR for historical books , in: Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on, 26-29 July 2009, Barcelona.

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Abstract

The aim of this work is to propose a new approach to the recognition of historical texts by providing an adaptive mechanism that automatically tunes itself to a specific book. The system is based on clustering together all the similar words in a book/text and simultaneously handling entire class. The paper describes the architecture of such a system and new algorithms that have been developed for robust word image comparison (including registration, optical flow based distortion compensation, and adaptive binarization). Results for a large dataset are presented as well. Over 23% recognition improvement is demonstrated.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: historical book, image recognition, optical character recognition, word-based adaptive OCR.
Schools: Schools > School of Computing, Science and Engineering
Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre (SIRC)
Journal or Publication Title: Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
Publisher: IEEE
Refereed: Yes
Related URLs:
Funders: Non funded research
Depositing User: S Rafiq
Date Deposited: 19 Jun 2014 10:43
Last Modified: 30 Nov 2015 23:58
URI: http://usir.salford.ac.uk/id/eprint/31898

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