Word-Based Adaptive OCR for Historical Books

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.

• Type: Conference
• Year: 2009
• Where: ICDAR
• Authors: Vladimir Kluzner, Asaf Tzadok, Yuval Shimony, Eugene Walach, Apostolos Antonacopoulos
• Keywords: Adaptive Mechanism, Document Analysis, ICDAR 2009, Robust Word Image, flow Based Distortion