Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	Juli 2018
Genre:	Naturwissensch., Medizin, Technik
	Applications of Graph Theory and Complex Networks / Artificial Intelligence / B / Complex analysis, complex variables / Computational Intelligence / Computer Vision / engineering / Graph Theory / Image processing / Image Processing and Computer Vision / Kombinatorik und Graphentheorie / Mathematical physics / Optical data processing / Physics mehr...
ISBN:	9783319849126
EAN-Code:	9783319849126
Verlag:	Springer EN
Einband:	Kartoniert
Sprache:	English
Serie:	#124 - Intelligent Systems Reference Library
Dimensionen:	H 235 mm / B 155 mm / D
Gewicht:	688 gr
Seiten:	431
Illustration:	XVII, 431 p. 354 illus., 301 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

This book introduces the fundamentals of computer vision (CV), with a focus on extracting useful information from digital images and videos. Including a wealth of methods used in detecting and classifying image objects and their shapes, it is the first book to apply a trio of tools (computational geometry, topology and algorithms) in solving CV problems, shape tracking in image object recognition and detecting the repetition of shapes in single images and video frames. Computational geometry provides a visualization of topological structures such as neighborhoods of points embedded in images, while image topology supplies us with structures useful in the analysis and classi¿cation of image regions. Algorithms provide a practical, step-by-step means of viewing image structures. The implementations of CV methods in Matlab and Mathematica, classi¿cation of chapter problems with the symbols (easily solved) and (challenging) and its extensive glossary of key words, examples and connections with the fabric of CV make the book an invaluable resource for advanced undergraduate and ¿rst year graduate students in Engineering, Computer Science or Applied Mathematics. It offers insights into the design of CV experiments, inclusion of image processing methods in CV projects, as well as the reconstruction and interpretation of recorded natural scenes.