000 03857nam a22004935i 4500
001 978-3-642-53845-2
003 DE-He213
005 20200420220216.0
007 cr nn 008mamaa
008 140128s2014 gw | s |||| 0|eng d
020 _a9783642538452
_9978-3-642-53845-2
024 7 _a10.1007/978-3-642-53845-2
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aPeters, James F.
_eauthor.
245 1 0 _aTopology of Digital Images
_h[electronic resource] :
_bVisual Pattern Discovery in Proximity Spaces /
_cby James F. Peters.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2014.
300 _aXVI, 411 p. 250 illus., 158 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v63
505 0 _aPreface -- 1 Topology of Digital Images: Basic Ingredients -- 2 Structures Arising from Sets of Pixels -- 3 Visualisations and Covers -- 4 Linear Filtering and Visual Patterns in Images -- 5 Edges, Lines, Ridges, and Nearness Structures -- 6 Corners and Symmetric Proximity -- 7 Separation of Image Regions and Set Patterns -- 8 Descriptive Raster Spaces -- 9 Component Analysis and Uniform Spaces -- 10 Shapes and Shape Set Patterns -- 11 Texture and Texture Set Patterns -- 12 Pattern-Based Picture Classification -- 13 Appendix: Matlab and Mathematica Scripts -- 14 Notes and Further Readings.
520 _aThis book carries forward recent work on visual patterns and structures in digital images and introduces a near set-based a topology of digital images. Visual patterns arise naturally in digital images viewed as sets of non-abstract points endowed with some form of proximity (nearness) relation. Proximity relations make it possible to construct uniform topolo- gies on the sets of points that constitute a digital image. In keeping with an interest in gaining an understanding of digital images themselves as a rich source of patterns, this book introduces the basics of digital images from a computer vision perspective. In parallel with a computer vision perspective on digital images, this book also introduces the basics of prox- imity spaces. Not only the traditional view of spatial proximity relations but also the more recent descriptive proximity relations are considered. The beauty of the descriptive proximity approach is that it is possible to discover visual set patterns among sets that are non-overlapping and non- adjacent spatially. By combining the spatial proximity and descriptive< proximity approaches, the search for salient visual patterns in digital im- ages is enriched, deepened and broadened. A generous provision of Matlab and Mathematica scripts are used in this book to lay bare the fabric and essential features of digital images for those who are interested in finding visual patterns in images. The combination of computer vision techniques and topological methods lead to a deep understanding of images.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aImage processing.
650 0 _aComputational intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aImage Processing and Computer Vision.
650 2 4 _aArtificial Intelligence (incl. Robotics).
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642538445
830 0 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v63
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-53845-2
912 _aZDB-2-ENG
942 _cEBK
999 _c51629
_d51629