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Título : | Recognition-free Retrieval of Old Arabic Document Images |
Otros títulos : | Recuperación de documentos árabes antiguos a partir de imágenes sin usar reconocimiento de caracteres |
Autor : | Sari, Toufik Kefali, Abderrahmane |
Palabras clave : | Keywords. Document retrieval, Arabic handwriting recognition, approximate string matching, document analysis. |
Fecha de publicación : | 13-dic-2011 |
Editorial : | Revista Computación y Sistemas; Vol. 15 No. 2 |
Citación : | Revista Computación y Sistemas; Vol. 15 No. 2 |
Citación : | Revista Computación y Sistemas;Vol. 15 No.2 |
Resumen : | Abstract. Searching of old document images is a relevant issue today. In this paper, we tackle the problem of old Arabic document images retrieval which form a good part of our heritage and possess an inestimable scientific and cultural richness. We propose an approach for indexing and searching degraded document images without recognizing the textual patterns in order to avoid the high cost and the difficult effort of the optical character recognition (OCR). Our basic idea consists in casting the problem of document images retrieval from the field of document analysis to the field of information retrieval. Thus, we can combine symbolic notation and semic representation and exploit techniques from the two fields, in particular, the techniques of suffix trees and approximate string matching. Each document of the collection is assigned an ASCII file of word codes. Words are represented by their topological features, namely, ascenders, descenders, etc. So, instead of searching in the image, we look for word codes in the corresponding file code. The tests performed on two types of documents, Arabic historical documents and Algerian postal envelopes, have showed good performance of the proposed approach. |
URI : | http://www.repositoriodigital.ipn.mx/handle/123456789/14855 |
ISSN : | 1405-5546 |
Aparece en las colecciones: | Revistas |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
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195_ART. 5_CyS_210.pdf | 1.28 MB | Adobe PDF | Visualizar/Abrir |
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