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Foundations of computer vision = com...

Peters, James F.

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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Foundations of computer vision/ by James F. Peters.
Reminder of title:	computational geometry, visual image structures and object shape detection /
Author:	Peters, James F.
Published:	Cham :Springer International Publishing : : 2017.,
Description:	xvii, 431 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Basics Leading to Machine Vision -- Working with Pixels -- Visualising Pixel Intensity Distributions -- Linear Filtering -- Edges, Lines, Corners, Gaussian kernel and Voronoi 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?.
Contained By:	Springer eBooks
Subject:	Computer vision. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-52483-2
ISBN:	9783319524832

Foundations of computer vision = computational geometry, visual image structures and object shape detection /
Peters, James F.

Foundations of computer visioncomputational geometry, visual image structures and object shape detection /[electronic resource] :by James F. Peters. - Cham :Springer International Publishing :2017. - xvii, 431 p. :ill. (some col.), digital ;24 cm. - Intelligent systems reference library,v.1241868-4394 ;. - Intelligent systems reference library ;v.124..

Basics Leading to Machine Vision -- Working with Pixels -- Visualising Pixel Intensity Distributions -- Linear Filtering -- Edges, Lines, Corners, Gaussian kernel and Voronoi 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?.

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.

ISBN: 9783319524832

Standard No.: 10.1007/978-3-319-52483-2doiSubjects--Topical Terms:

540671
Computer vision.

LC Class. No.: TA1634

Dewey Class. No.: 006.37

Foundations of computer vision = computational geometry, visual image structures and object shape detection /
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245 1 0 $a Foundations of computer vision $h [electronic resource] : $b computational geometry, visual image structures and object shape detection / $c by James F. Peters.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a xvii, 431 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Intelligent systems reference library, $x 1868-4394 ; $v v.124
505 0 $a Basics Leading to Machine Vision -- Working with Pixels -- Visualising Pixel Intensity Distributions -- Linear Filtering -- Edges, Lines, Corners, Gaussian kernel and Voronoi 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?.
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.
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