Combinatorial Image Analysis: Lecture Notes in Computer Science, cartea 9448
Editat de Reneta P. Barneva, Bhargab B. Bhattacharya, Valentin E. Brimkoven Limba Engleză Paperback – 4 noi 2015
The 24 revised full papers and 2 invited papers presentedwere carefully reviewed and selected from numerous submissions. The workshopprovides theoretical foundations and methods for solving problems from variousareas of human practice. In contrast to traditional approaches to imageanalysis which implement continuous models, float arithmetic and rounding,combinatorial image analysis features discrete modelsusing integer arithmetic.The developed algorithms are based on studying combinatorial properties ofclasses of digital images, and often appear to be more efficient and accuratethan those based on continuous models.
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Specificații
ISBN-13: 9783319261447
ISBN-10: 3319261444
Pagini: 380
Ilustrații: XIII, 363 p. 177 illus. in color.
Dimensiuni: 155 x 235 x 21 mm
Greutate: 0.58 kg
Ediția:1st edition 2015
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
ISBN-10: 3319261444
Pagini: 380
Ilustrații: XIII, 363 p. 177 illus. in color.
Dimensiuni: 155 x 235 x 21 mm
Greutate: 0.58 kg
Ediția:1st edition 2015
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
Public țintă
ResearchCuprins
Theoretical Foundations of Combinatorial Image Analysis.- Digital Geometry and Topology.- Grammars and Other Formal Tools.- From Theory to Applications.
Textul de pe ultima copertă
This volume constitutes the refereed proceedings of the17th International Workshop on Combinatorial Image Analysis, IWCIA 2015, heldin Kolkata, India, in November 2015.
The 24 revised full papers and 2 invited papers presentedwere carefully reviewed and selected from numerous submissions. The workshopprovides theoretical foundations and methods for solving problems from variousareas of human practice. In contrast to traditional approaches to imageanalysis which implement continuous models, float arithmetic and rounding,combinatorial image analysis features discrete modelsusing integer arithmetic.The developed algorithms are based on studying combinatorial properties ofclasses of digital images, and often appear to be more efficient and accuratethan those based on continuous models.
The 24 revised full papers and 2 invited papers presentedwere carefully reviewed and selected from numerous submissions. The workshopprovides theoretical foundations and methods for solving problems from variousareas of human practice. In contrast to traditional approaches to imageanalysis which implement continuous models, float arithmetic and rounding,combinatorial image analysis features discrete modelsusing integer arithmetic.The developed algorithms are based on studying combinatorial properties ofclasses of digital images, and often appear to be more efficient and accuratethan those based on continuous models.