Name: Symbol Spotting in Digital Libraries: Focused Retrieval Over Graphic-Rich Document Collections (en Inglés)
Price: 296189.00 COP
Availability: InStock
Author: Rusiñol, Marçal ; Lladós, Josep
ISBN: 9781447161790

portada Symbol Spotting in Digital Libraries: Focused Retrieval Over Graphic-Rich Document Collections (en Inglés)

Symbol Spotting in Digital Libraries: Focused Retrieval Over Graphic-Rich Document Collections (en Inglés)

Formato

Libro Físico

Autor

Josep Lladós

Marçal Rusiñol

Editorial

Springer

Idioma

Inglés

N° páginas

180

Encuadernación

Tapa Blanda

Dimensiones

23.4 x 15.6 x 1.1 cm

Peso

0.28 kg.

ISBN13

9781447161790

Categorías

Medios de almacenamiento y dispositivos periféricos
Recuperación de información
Administración del sistema
Reconocimiento de formas
Visión por ordenador

Symbol Spotting in Digital Libraries: Focused Retrieval Over Graphic-Rich Document Collections (en Inglés)

Josep Lladós (Autor) · Marçal Rusiñol (Autor) · Springer · Tapa Blanda

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Reseña del libro "Symbol Spotting in Digital Libraries: Focused Retrieval Over Graphic-Rich Document Collections (en Inglés)"

Pattern recognition basically deals with the recognition of patterns, shapes, objects, things in images. Document image analysis was one of the very ?rst applications of pattern recognition and even of computing. But until the 1980s, research in this ?eld was mainly dealing with text-based documents, including OCR (Optical Character Recognition) and page layout analysis. Only a few people were looking at more speci?c documents such as music sheet, bank cheques or forms. The community of graphics recognition became visible in the late 1980s. Their speci?c interest was to recognize high-level objects represented by line drawings and graphics. The speci?c pattern recognition problems they had to deal with was raster-to-graphics conversion (i.e., recognizing graphical primitives in a cluttered pixel image), text-graphics separation, and symbol recognition. The speci?c problem of symbol recognition in graphical documents has received a lot of attention. The symbols to be recognized can be musical notation, electrical symbols, architectural objects, pictograms in maps, etc. At ?rst glance, the symbol recognition problems seems to be very similar to that of character recognition; - ter all, characters are basically a subset of symbols. Therefore, the large know-how in OCR has been extensively used in graphical symbol recognition: starting with segmenting the document to extract the symbols, extracting features from the s- bols, and then recognizing them through classi?cation or matching, with respect to a training/learning set.