Foundations of computer vision : computational geometry, visual image structures and object shape detection

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 ge...

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Bibliographic Details
Main Author: Peters, James F., (Author)
Format: eBook
Language: English
Published: Cham, Switzerland : Springer, 2017.
Series: Intelligent systems reference library ; v. 124.
Subjects:
Computer vision.
elektronické knihy
electronic books
ISBN: 9783319524832
9783319524818
Physical Description: 1 online resource (xvii, 431 pages) : illustrations (some color)

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100 1 |a Peters, James F.,  |e author. 
245 1 0 |a Foundations of computer vision :  |b computational geometry, visual image structures and object shape detection /  |c James F. Peters. 
264 1 |a Cham, Switzerland :  |b Springer,  |c 2017. 
300 |a 1 online resource (xvii, 431 pages) :  |b illustrations (some color) 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
338 |a online zdroj  |b cr  |2 rdacarrier 
490 1 |a Intelligent systems reference library,  |x 1868-4394 ;  |v volume 124 
504 |a Includes bibliographical references and index. 
505 0 |a Basics Leading to Machine Vision -- Working with Pixels -- Visualising Pixel Intensity Distributions -- Linear Filtering -- Edges, Lines, Corners, Gaussian kernel and Voronoï Meshes -- Delaunay Mesh Segmentation -- Video Processing. An Introduction to Real-Time and Offline Video Analysis -- Lowe Keypoints, Maximal Nucleus Clusters, Contours and Shapes -- Postscript. Where Do Shapes fit into the Computer Vision Landscape?. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a 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 classification of image regions. Algorithms provide a practical, step-by-step means of viewing image structures. The implementations of CV methods in Matlab and Mathematica, classification 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 first 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. 
590 |a SpringerLink  |b Springer Complete eBooks 
650 0 |a Computer vision. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
776 0 8 |i Print version:  |a Peters, James F.  |t Foundations of computer vision.  |d Cham, Switzerland : Springer, 2017  |z 331952481X  |z 9783319524818  |w (OCoLC)966556391 
830 0 |a Intelligent systems reference library ;  |v v. 124.  |x 1868-4394 
856 4 0 |u https://proxy.k.utb.cz/login?url=https://link.springer.com/10.1007/978-3-319-52483-2  |y Plný text 
992 |c NTK-SpringerENG 
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993 |x NEPOSILAT  |y EIZ 

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