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Symbol Spotting in Digital Libraries

Symbol Spotting in Digital Libraries

Autorzy
Wydawnictwo Springer Nature Customer Service Center GmbH
Data wydania 01/01/2010
Wydanie Pierwsze
Liczba stron 180
Forma publikacji książka w twardej oprawie
Język angielski
ISBN 9781849962070
Kategorie Wizja komputerowa
15.00 PLN (z VAT)
$3.37 / €3.22 / £2.79 /
Produkt dostępny
Dostawa 2 dni
Ilość
Do schowka

Opis książki

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.

Symbol Spotting in Digital Libraries

Spis treści

Introduction.- State of the Art in Symbol Spotting.- Part I: On the Use of Photometric.- Descriptors for Symbol Spotting.- Symbol Spotting for Document Categorization.- Part II: On the Use of Geometric and Structural Constraints for Symbol Spotting.- Vectorial Signatures for Symbol Recognition and Spotting.- Symbol Spotting Through Prototype-based Search.- A Relational Indexing Method for Symbol Spotting.- Part III: A Performance Evaluation Protocol for Symbol Spotting Systems.- Performance Evaluation of Symbol Spotting Systems.- Conclusions.

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