LEADER 05950nam 2200709 a 450 001 9911004824103321 005 20200520144314.0 010 $a1-61583-698-5 010 $a0-8194-7866-0 024 7 $a10.1117/3.501104 035 $a(CKB)2470000000002936 035 $a(EBL)728518 035 $a(OCoLC)435933441 035 $a(SSID)ssj0000381558 035 $a(PQKBManifestationID)11938001 035 $a(PQKBTitleCode)TC0000381558 035 $a(PQKBWorkID)10391027 035 $a(PQKB)11211533 035 $a(MiAaPQ)EBC728518 035 $a(CaBNVSL)gtp00535563 035 $a(SPIE)9780819478665 035 $a(PPN)237266660 035 $a(EXLCZ)992470000000002936 100 $a20030604d2003 uy 0 101 0 $aeng 135 $aurbn||||m|||a 181 $ctxt 182 $cc 183 $acr 200 10$aHands-on morphological image processing /$fEdward R. Dougherty, Roberto A. Lotufo 210 $aBellingham, Wash. $cSPIE Optical Engineering Press$d2003 215 $a1 online resource (289 p.) 225 1 $aTutorial texts in optical engineering ;$vv. TT 59 300 $aDescription based upon print version of record. 311 $a0-8194-4720-X 320 $aIncludes bibliographical references and index. 327 $aPreface -- List of Symbols -- 1. Binary Erosion and Dilation -- 1.1 Introduction -- 1.2 Euclidean and Discrete Binary Images -- 1.3 Erosion -- 1.4 Dilation -- 1.5 Algebraic Properties -- 1.6 Filter Properties -- 1.7 Relationship to Set Operations -- 1.8 Bounded Operators -- 1.9 Exercises -- 1.10 Laboratory Experiments -- 1.11 References -- 327 $a2. Binary Opening and Closing -- 2.1 Opening -- 2.2 Closing -- 2.3 Filter Properties -- 2.4 Application of Opening and Closing Filters -- 2.5 Alternating Sequential Filters -- 2.6 Invariance -- 2.7 T-Openings -- 2.8 Demonstration -- 2.9 Exercises -- 2.10 Laboratory Experiments -- 2.11 References -- 327 $a3. Morphological Processing of Binary Images -- 3.1 Pixel Regions -- 3.2 Boundary Detection -- 3.3 Reconstruction -- 3.4 Conditional Dilation -- 3.5 Marker Selection in Reconstruction -- 3.6 Reconstructive T-opening -- 3.7 Logical Openings -- 3.8 Logical Structural Filters -- 3.9 Connected Operators -- 3.10 Skeletonization -- 3.11 Distance Transform -- 3.12 Geodesic Distance Transform -- 3.13 Exercises -- 3.14 Laboratory Experiments -- 3.15 References -- 327 $a4. Hit-or-Miss Transform -- 4.1 The Transform -- 4.2 Object Recognition -- 4.3 Thinning -- 4.4 Pruning -- 4.5 Exercises -- 4.6 Laboratory Experiments -- 4.7 References -- 327 $a5. Gray-Scale Morphology -- 5.1 Mathematical Preliminaries -- 5.2 Gray-Scale Erosion -- 5.3 Gray-Scale Dilation -- 5.4 Algebraic Properties -- 5.5 Filter Properties -- 5.6 Umbra Transform -- 5.7 Flat Structuring Elements -- 5.8 Gray-Scale Morphology for Discrete Images -- 5.9 Gray-Scale Morphology for Discrete Bounded Signals -- 5.10 Gray-Scale Opening and Closing -- 5.11 Exercises -- 5.12 Laboratory Experiments -- 5.13 References -- 327 $a6. Morphological Processing of Gray-Scale Images -- 6.1 Morphological Gradient -- 6.2 Top-Hat Transform -- 6.3 Gray-Scale Alternating Sequential Filters -- 6.4 Gray-Scale Morphological Reconstruction -- 6.5 Flat Zones and Connected Filters -- 6.6 Gray-Scale Reconstructive Opening -- 6.7 Connected Alternating Sequential Filters -- 6.8 Image Extrema -- 6.9 Markers From Regional Maxima of Filtered Images -- 6.10 Extinction Values -- 6.11 Demonstration -- 6.12 Exercises -- 6.13 Laboratory Experiments -- 6.14 References -- 327 $a7. Morphological Segmentation Watershed -- 7.1 Watershed From Markers -- 7.2 Watershed, Voronoi Diagram and SKIZ -- 7.3 Segmentation of Overlapped Convex Cells -- 7.4 Inner and Outer Markers -- 7.5 Hierarchical Watershed Transform -- 7.6 Watershed Transform Algorithms -- 7.7 Demonstrations -- 7.8 Exercises -- 7.9 Laboratory Experiments -- 7.10 References -- 327 $a8. Granulometries -- 8.1 Granulometries Generated by a Single Opening -- 8.2 Discrete Size Distributions -- 8.3 The Open and Discrete-Size Transforms -- 8.4 Granulometries on Random Binary Images -- 8.5 Granulometric Classification -- 8.6 General Granulometries -- 8.7 Logical Granulometries -- 8.8 Discrete Granulometric Bandpass Filters -- 8.9 Gray-Scale Granulometries -- 8.10 Exercises -- 8.11 Laboratory Experiments -- 8.12 References -- 327 $a9. Automatic Design of Morphological Operators -- 9.1 Boolean Functions -- 9.2 Morphological Representation -- 9.3 Optimal W-Operators -- 9.4 Design of Optimal W-Operators -- 9.5 Optimal Increasing Filters -- 9.6 Differencing Filters -- 9.7 Resolution Conversion -- 9.8 Multiresolution Analysis -- 9.9 Aperture Filters -- 9.10 Relation to Pattern Recognition -- 9.11 Exercises -- 9.12 References --Index. 330 $aMorphological image processing, now a standard part of the imaging scientist's toolbox, can be applied to a wide range of industrial applications. Concentrating on applications, this book shows how to analyze a problem and then develop successful algorithms based on the analysis. The book is hands-on in a very real sense: readers can download a demonstration toolbox of techniques and images from the web so they can process the images according to examples in the text. 410 0$aTutorial texts in optical engineering ;$vv. TT 59. 606 $aImage processing$xMathematics 606 $aMorphisms (Mathematics) 615 0$aImage processing$xMathematics. 615 0$aMorphisms (Mathematics) 676 $a621.36/7 700 $aDougherty$b Edward R$0731599 701 $aLotufo$b Roberto A$01823146 712 02$aSociety of Photo-optical Instrumentation Engineers. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911004824103321 996 $aHands-on morphological image processing$94389639 997 $aUNINA