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Symbol Spotting in Digital Libraries: Focused Retrieval over Graphic-rich Docume

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Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
ISBN-13
9781447161790
Book Title
Symbol Spotting in Digital Libraries
ISBN
9781447161790
Subject Area
Computers, Technology & Engineering, Language Arts & Disciplines
Publication Name
Symbol Spotting in Digital Libraries : Focused Retrieval over Graphic-Rich Document Collections
Publisher
Springer London, The Limited
Item Length
9.3 in
Subject
Computer Graphics, Library & Information Science / Archives & Special Libraries, Databases / General, Computer Vision & Pattern Recognition, Imaging Systems
Publication Year
2014
Type
Textbook
Format
Trade Paperback
Language
English
Author
Josep Lladós, Marçal Rusiñol
Item Weight
16 Oz
Item Width
6.1 in
Number of Pages
Xiv, 180 Pages

About this product

Product Information

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.

Product Identifiers

Publisher
Springer London, The Limited
ISBN-10
1447161793
ISBN-13
9781447161790
eBay Product ID (ePID)
211934260

Product Key Features

Number of Pages
Xiv, 180 Pages
Language
English
Publication Name
Symbol Spotting in Digital Libraries : Focused Retrieval over Graphic-Rich Document Collections
Publication Year
2014
Subject
Computer Graphics, Library & Information Science / Archives & Special Libraries, Databases / General, Computer Vision & Pattern Recognition, Imaging Systems
Type
Textbook
Subject Area
Computers, Technology & Engineering, Language Arts & Disciplines
Author
Josep Lladós, Marçal Rusiñol
Format
Trade Paperback

Dimensions

Item Weight
16 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
Dewey Edition
22
Reviews
From the reviews: "This monograph is a clearly written and accessible survey and framework for the field, and it should prove useful to researchers and students in computer vision, pattern recognition, and related fields. It would also be instructive for advanced practitioners in these areas ... . References are provided at the end of each chapter for researchers who need or want to refer to the primary literature. In short, this book is a concise, readable, and informative resource on its specialized problem domain and related areas." (R. M. Malyankar, ACM Computing Reviews, October, 2010)
Number of Volumes
1 Vol.
Illustrated
Yes
Dewey Decimal
025.04
Lc Classification Number
Qa76.9.D3
Table of Content
State-of-the-Art in Symbol Spotting.- On the Use of Photometric Descriptors for Symbol Spotting.- Symbol Spotting for Document Categorization.- 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.- A Performance Evaluation Protocol for Symbol Spotting Systems.- Performance Evaluation of Symbol Spotting Systems.- Conclusions.
Copyright Date
2010

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