Word-Based adaptive OCR for historical books

Kluzner, V; Tzadok, A; Shimony, Y; Walach, E; Antonacopoulos, A

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.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on
• Start Date: Jul 26, 2009
• End Date: Jul 29, 2009
• Publication Date: Jan 1, 2009
• Deposit Date: Jun 19, 2014
• Book Title: 2009 10th International Conference on Document Analysis and Recognition
• DOI: https://doi.org/10.1109/ICDAR.2009.133
• Keywords: historical book,; image recognition,; optical character recognition,; word-based adaptive OCR.
• Publisher URL: http://dx.doi.org/10.1109/ICDAR.2009.133
• Related Public URLs: http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5277471
• Additional Information: Event Type : Conference