Automatic Feature Extraction and Recognition for Digital Access of Books of the Renaissance
Antique printed books constitute a heritage that should be preserved and used. With novel digitising techniques is now possible to have these books stored in digital format and accessible to a wider public. However it remains the problem of how to use them. DEBORA (Digital accEss to BOoks of the RenAissance) is a European project that aims to develop a system to interact with these books through world-wide networks. The main issue is to build a database accessible through client computers. That will require to built accompanying metadata that should characterise different components of the books as illuminated letters, banners, figures and key words in order to simplify and speed up the remote access. To solve these problems, digital image analysis algorithms regarding filtering, segmentation, separation of text from non-text, lines and word segmentation and word recognition were developed. Some novel ideas are presented and illustrated through examples.
KeywordsWord Recognition Binary Image Document Image Mathematical Morphology Word Segmentation
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- 2.Beucher S., 1996, Pré-traitement morphologique d’images de plis postaux, 4 éme Colloque National Sur L’ecrit Et Le Document-Cned’96, Nantes.Google Scholar
- 3.Bhat D., 1998, An Evolutionary Measure for Image Matching, in ICPR’98 — Proc. 14th Int. Conf. On Pattern Recognition, vol. I, 850–852, Brisbane, Australia.Google Scholar
- 6.Guillevic D., Suen C.Y., 1997, HMM Word Recognition Engine, in ICDAR’97 — Proc. 4th Int. Conf. on Document Analysis and Recognition, vol. 2, 544–547, Ulm, GermanyGoogle Scholar
- 7.He S., Abe N., 1996, A Clustering-Based Approach to the Separation of Text Strings from Mixed Text/Graphics Documents, Proceedings of ICPR’ 96, Vienna.Google Scholar
- 9.Marcolino A., Ramos V., Ramalho M., Caldas Pinto J., 2000, Line and Word Matching in Old Documents, submitted to SIARP’2000 — V Ibero-American Symposium on Pattern Recognition, Lisboa.Google Scholar
- 10.Mengucci M., Granado I., Muge F., Caldas Pinto J.R., 2000, A Methodology Based on Mathematical Morphology for the Extraction of Text and Figures from Ancient Books, RecPad 2000, pp 471–476 Porto, 11-12 May 2000, Portugal.Google Scholar
- 11.Parodi P., Piccioli G., 1996, An Efficient Pre-Processing of Mixed-Content Document Images for OCR Systems, Proceedings of ICPR’ 96, Vienna.Google Scholar
- 12.Ramos V., 2000, An Evolutionary Measure for Image Matching — Extensions to Binary Image Matching, Internal Technical Report, CVRM/IST, Lisboa.Google Scholar
- 13.Serra J., 1982, Image Analysis and Mathematical Morphology, Academic Press, London.Google Scholar
- 16.Srihari, et al, Document Image Understanding, http://www.cedar.buffalo.edu/ Publications/TechReps/Survey/, CEDAR-TR-92-1, 1992.