Challenges in OCR of Dev anagari Documents
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Adapting the Tesseract open source OCR engine for multilingual OCR
Proceedings of the International Workshop on Multilingual OCR
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In this paper we present methodologies for three important tasks that will eventually enable digital access of multilingual Indian document images. Firstly, we describe several document image analysis techniques necessary to prepare Devanagari document images for OCR. The second task is OCR for machine printed Devanagari words without the help of a lexicon. We describe the OCR methodology and show how it is being extended to other Indian languages. Finally, we describe a verstile platform that facilitates automatic segmentation of document images in multiple Indian languages and an interface to capture the ground truth corresponding to the text. We use transliterated English text and virtual keyboards in a range of Indian languages for this purpose. The multi-lingual data entry capabilities of the tool and its underlying UNICODE data representation within a structured XML document also allow users to annotate passages of text in one language in other languages using a markup scheme to switch between scripts. Text and annotations are rendered in the appropriate scripts as the text is being annotated, thus providing users prompt and natural feedback. The XML back-end allows meta-data to be recorded describing the annotated document.