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008			170327s2017 sz a ob 001 0 eng d
020			_a3319524836 _q(electronic bk.)
020			_a9783319524832 _q(electronic bk.)
020			_z331952481X
020			_z9783319524818
040			_aGW5XE _cGW5XE _dYDX _dUAB _dIOG _dOCLCF _dAZU _dUPM _dESU _dJBG _dIAD _dICW _dICN _dVT2 _dOTZ _dU3W _dES-MaUEC _bspa
050		4	_aTA1634 _b.P484 2017 EB
100	1		_aPeters, James F., _eautor _998829
245	1	0	_aFoundations of computer vision : _bcomputational geometry, visual image structures and object shape detection _cJames F. Peters.
264		1	_aCham, Switzerland _bSpringer _c2017.
300			_a1 recurso en línea (xvii, 431 páginas) _bilustraciones (algunas a color)
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	0		_aIntelligent systems reference library _x1868-4394 _vvolume 124
500			_aSpringerLink _bSpringer Engineering eBooks 2017 English+International
504			_aIncluye referencias bibliográficas e índice
505	0		_aBasics 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	3		_aThis 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.
650		7	_aVisión por ordenador _2embne _0(OCoLC)fst00872687 _0 _9159793
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=http://link.springer.com/10.1007/978-3-319-52483-2 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
988			_aEBOOK, asignarmaterias, EBSPRINGER_2017C
998			_b02/2018 _dz _e- _zSI
999			_c95651 _d95651 _x1