Foundations of Computer Vision (Record no. 80693)
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000 -LEADER | |
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fixed length control field | 03870nam a22005655i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-319-52483-2 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20220801222352.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 170318s2017 sz | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783319524832 |
-- | 978-3-319-52483-2 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 006.3 |
100 1# - AUTHOR NAME | |
Author | Peters, James F. |
245 10 - TITLE STATEMENT | |
Title | Foundations of Computer Vision |
Sub Title | Computational Geometry, Visual Image Structures and Object Shape Detection / |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2017. |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | XVII, 431 p. 354 illus., 301 illus. in color. |
490 1# - SERIES STATEMENT | |
Series statement | Intelligent Systems Reference Library, |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | 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?. |
520 ## - SUMMARY, ETC. | |
Summary, etc | 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. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | https://doi.org/10.1007/978-3-319-52483-2 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
264 #1 - | |
-- | Cham : |
-- | Springer International Publishing : |
-- | Imprint: Springer, |
-- | 2017. |
336 ## - | |
-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
-- | cr |
-- | rdacarrier |
347 ## - | |
-- | text file |
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-- | rda |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computational intelligence. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer vision. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Graph theory. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computational Intelligence. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer Vision. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial Intelligence. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Graph Theory. |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
-- | 1868-4408 ; |
912 ## - | |
-- | ZDB-2-ENG |
912 ## - | |
-- | ZDB-2-SXE |
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