Document Image Analysis Current Trends and Challenges in Graphics Recognition /

The book focuses on one of the key issues in document image processing - graphical symbol recognition, which is a sub-field of the larger research domain of pattern recognition. It covers several approaches: statistical, structural and syntactic, and discusses their merits and demerits considering t...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Santosh, K.C (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2018.
Έκδοση:1st ed. 2018.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Santosh, K.C.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Document Image Analysis  |h [electronic resource] :  |b Current Trends and Challenges in Graphics Recognition /  |c by K.C. Santosh. 
250 |a 1st ed. 2018. 
264 1 |a Singapore :  |b Springer Singapore :  |b Imprint: Springer,  |c 2018. 
300 |a XX, 174 p. 70 illus., 46 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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505 0 |a Chapter 1. Document Image Processing: Graphics Recognition -- Chapter 2. Graphical Symbol Recognition Systems, Applications and Validation -- Chapter 3. Statistical Approaches -- Chapter 4. Structural and Syntactic Approaches -- Chapter 5. Hybrid Approaches -- Chapter 6. Challenges. 
520 |a The book focuses on one of the key issues in document image processing - graphical symbol recognition, which is a sub-field of the larger research domain of pattern recognition. It covers several approaches: statistical, structural and syntactic, and discusses their merits and demerits considering the context. Through comprehensive experiments, it also explores whether these approaches can be combined. The book presents research problems, state-of-the-art methods that convey basic steps as well as prominent techniques, evaluation metrics and protocols, and research standpoints/directions that are associated with it. However, it is not limited to straightforward isolated graphics (visual patterns) recognition; it also addresses complex and composite graphical symbols recognition, which is motivated by real-world industrial problems. 
650 0 |a Pattern recognition. 
650 0 |a Optical data processing. 
650 0 |a Computer graphics. 
650 1 4 |a Pattern Recognition.  |0 http://scigraph.springernature.com/things/product-market-codes/I2203X 
650 2 4 |a Image Processing and Computer Vision.  |0 http://scigraph.springernature.com/things/product-market-codes/I22021 
650 2 4 |a Computer Graphics.  |0 http://scigraph.springernature.com/things/product-market-codes/I22013 
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856 4 0 |u https://doi.org/10.1007/978-981-13-2339-3  |z Full Text via HEAL-Link 
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950 |a Computer Science (Springer-11645)