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Symbol Spotting in Digital Libraries - Focused Retrieval over Graphic-rich Document Collections (Paperback, 2010 ed.)
Loot Price: R2,957
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Symbol Spotting in Digital Libraries - Focused Retrieval over Graphic-rich Document Collections (Paperback, 2010 ed.)
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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.
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