Overview
- Includes supplementary material: sn.pub/extras
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10225)
Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Included in the following conference series:
Conference proceedings info: ISMM 2017.
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About this book
The 36 revised full papers presented together with 4 short papers were carefully reviewed and selected from 53 submissions. The papers are organized in topical sections on algebraic theory, max-plus and max-min mathematics; discrete geometry and discrete topology; watershed and graph-based segmentation; trees and hierarchies; topological and graph-based clustering, classification and filtering; connected operators and attribute filters; PDE-based morphology; scale-space representations and nonlinear decompositions; computational morphology; object detection; and biomedical, material science and physical applications.
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Keywords
- discrete geometry
- machine learning
- neural networks
- optimization
- pattern recognition
- algorithmics
- continuous morphology
- curve tracing
- data-structure
- discrete topology
- geometric image processing
- graph theory
- hypergraphs
- image processing
- image segmentation
- mathematical morphology
- minimal path
- partial differential equations
- particle tracking
- topological data analysis
- algorithm analysis and problem complexity
Table of contents (40 papers)
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Algebraic Theory, Max-Plus and Max-Min Mathematics
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Discrete Geometry and Discrete Topology
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Watershed and Graph-Based Segmentation
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Trees and Hierarchies
Other volumes
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Mathematical Morphology and Its Applications to Signal and Image Processing
Editors and Affiliations
Bibliographic Information
Book Title: Mathematical Morphology and Its Applications to Signal and Image Processing
Book Subtitle: 13th International Symposium, ISMM 2017, Fontainebleau, France, May 15–17, 2017, Proceedings
Editors: Jesús Angulo, Santiago Velasco-Forero, Fernand Meyer
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-319-57240-6
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Softcover ISBN: 978-3-319-57239-0Published: 12 April 2017
eBook ISBN: 978-3-319-57240-6Published: 07 April 2017
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XIV, 500
Number of Illustrations: 204 b/w illustrations
Topics: Image Processing and Computer Vision, Math Applications in Computer Science, Discrete Mathematics in Computer Science, Algorithm Analysis and Problem Complexity, Data Structures, Artificial Intelligence