Cover image for Mathematical Foundations of Image Processing and Analysis, Volume 2.
Mathematical Foundations of Image Processing and Analysis, Volume 2.
Title:
Mathematical Foundations of Image Processing and Analysis, Volume 2.
Author:
Pinoli, Jean-Charles.
ISBN:
9781118984567
Personal Author:
Edition:
1st ed.
Physical Description:
1 online resource (492 pages)
Series:
ISTE
Contents:
Cover -- Title Page -- Copyright -- Contents -- Preface -- Introduction -- PART 5: Twelve Main Geometrical Frameworks for Binary Images -- Chapter 21: The Set-Theoretic Framework -- 21.1. Paradigms -- 21.2. Mathematical concepts and structures -- 21.2.1. Mathematical disciplines -- 21.3. Main notions and approaches for IPA -- 21.3.1. Pixels and objects -- 21.3.2. Pixel and object separation -- 21.3.3. Local finiteness -- 21.3.4. Set transformations -- 21.4. Main applications for IPA -- 21.4.1. Object partition and object components -- 21.4.2. Set-theoretic separation of objects and object removal -- 21.4.3. Counting of separate objects -- 21.4.4. Spatial supports border effects -- 21.5. Additional comments -- Historical comments and references -- Bibliographic notes and additional readings -- Further topics and readings -- Some references on applications to IPA -- Chapter 22: The Topological Framework -- 22.1. Paradigms -- 22.2. Mathematical concepts and structures -- 22.2.1. Mathematical disciplines -- 22.2.2. Special classes of subsets of Rn -- 22.2.3. Fell topology for closed subsets -- 22.2.4. Hausdorff topology for compact subsets -- 22.2.5. Continuity and semi-continuity of set transformations -- 22.2.6. Continuity of basic set-theoretic and topological operations -- 22.3. Main notions and approaches for IPA -- 22.3.1. Topologies in the spatial domain Rn -- 22.3.2. The Lebesgue-(Čech) dimension -- 22.3.3. Interior and exterior boundaries -- 22.3.3.1. Topologically regular objects -- 22.3.4. Path-connectedness -- 22.3.5. Homeomorphic objects -- 22.4. Main applications to IPA -- 22.4.1. Topological separation of objects and object removal -- 22.4.1.1. (Path)-connected components -- 22.4.2. Counting of separate objects -- 22.4.3. Contours of objects -- 22.4.4. Metric diameter -- 22.4.5. Skeletons of proper objects.

22.4.6. Dirichlet-Voronoi's diagrams -- 22.4.7. Distance maps -- 22.4.8. Distance between objects -- 22.4.9. Spatial support's border effects -- 22.5. Additional comments -- Historical comments and references -- Bibliographic notes and additional readings -- Further topics and readings -- Some references on applications to IPA -- Chapter 23: The Euclidean Geometric Framework -- 23.1. Paradigms -- 23.2. Mathematical concepts and structures -- 23.2.1. Mathematical disciplines -- 23.2.2. Euclidean dimension -- 23.2.3. Matrices -- 23.2.4. Determinants -- 23.2.5. Eigenvalues, eigenvectors and trace of a matrix -- 23.2.6. Matrix norms -- 23.3. Main notions and approaches for IPA -- 23.3.1. Affine transformations -- 23.3.2. Special groups of affine transformations -- 23.3.3. Linear and affine sub-spaces and Grassmannians -- 23.3.4. Linear and affine spans -- 23.4. Main applications to IPA -- 23.4.1. Basic spatial transformations -- 23.4.1.1. Reflected objects -- 23.4.2. Hyperplanes -- 23.4.3. Polytopes -- 23.4.4. Minkowski addition and subtraction -- 23.4.5. Continuity and semi-continuities of Euclidean transformations -- 23.5. Additional comments -- Historical comments and references -- Commented bibliography and additional readings -- Further topics and readings -- Some references on applications to IPA -- Chapter 24: The Convex Geometric Framework -- 24.1. Paradigms -- 24.2. Mathematical concepts and structures -- 24.2.1. Mathematical disciplines -- 24.3. Main notions and approaches for IPA -- 24.3.1. Convex objects -- 24.3.1.1. Convex objects and extremal pixels -- 24.3.1.2. Convex objects and hyperplanes -- 24.3.1.3. Convex hulls -- 24.3.2. Hausdorff topology for compact convex objects -- 24.3.3. Compact poly-convex objects -- 24.3.4. Star-shaped objects -- 24.3.5. Simplices -- 24.4. Main applications to IPA.

24.4.1. Convex deficiency set and concavities -- 24.4.2. Functions related to convex and star-shaped objects -- 24.4.3. Delaunay triangulation -- 24.5. Additional comments -- Historical comments -- Bibliographic notes and additional readings -- Further topics and readings -- Some references on applications to IPA -- Chapter 25: The Morphological Geometric Framework -- 25.1. Paradigms -- 25.2. Mathematical concepts and structures -- 25.2.1. Mathematical disciplines -- 25.3. Mathematical notions and approaches for IPA -- 25.3.1. Morphological dilation and erosion -- 25.3.2. Morphological closing and opening -- 25.3.3. Set properties of morphological dilation, erosion, closing and opening -- 25.3.4. Morphological regular objects -- 25.3.5. Continuity of the morphological operations -- 25.4. Main notions and approaches for IPA -- 25.4.1. Morphological transformations -- 25.4.2. Parallel objects -- 25.4.3. Federer sets -- 25.5. Main applications to IPA -- 25.5.1. Object contours and morphological boundaries -- 25.5.2. Object filtering and morphological smoothing -- 25.5.3. Morphological skeleton -- 25.5.4. Ultimate erosion -- 25.5.5. Morphing -- 25.6. Additional comments -- Historical comments and references -- Bibliographic notes and additional readings -- Further topics and readings -- Applications to image processing and analysis -- Chapter 26: The Geometric and Topological Framework -- 26.1. Paradigms -- 26.2. Mathematical concepts and structures -- 26.2.1. Mathematical disciplines -- 26.2.2. Manifolds or locally Euclidean spaces -- 26.2.3. Manifolds with border -- 26.2.4. Submanifolds -- 26.2.5. Compact and closed manifolds -- 26.2.6. Lipschitz manifolds and Lipschitz sets -- 26.3. Mathematical approaches for IPA -- 26.3.1. Unit ball and unit cube, torii and annulii -- 26.3.2. Points, curves and surfaces -- 26.3.3. Hypersurfaces.

26.3.4. Homeomorphic and homotopic objects -- 26.4. Main applications to IPA -- 26.4.1. Contour -- 26.4.1.1. Contour in dimension 2 -- 26.4.1.2. Contour in dimension 3 -- 26.4.2. Topological content -- 26.4.3. The Lebesgue-(Čech) dimension of homeomorphic or homotopic objects -- 26.4.4. The Descartes-Euler-Poincaré's number and the Betti numbers -- 26.4.5. Some particular basic manifolds -- 26.5. Additional comments -- Historical comments and references -- Bibliographic notes and suggested readings -- Further topics and readings -- Some references on applications to Image Analysis -- Chapter 27: The Measure-Theoretic Geometric Framework -- 27.1. Paradigms -- 27.2. Mathematical concepts and structures -- 27.2.1. Mathematical disciplines -- 27.2.2. The Gauss measure -- 27.2.3. The Peano-Jordan measures -- 27.2.4. Measures and contents -- 27.2.5. Outer measures and Borel sets -- 27.2.6. Finite and σ-finite measures -- 27.2.7. Null sets, negligible sets and complete measures -- 27.2.8. Atoms and atomic measures -- 27.2.9. The n-dimensional Lebesgue measure -- 27.2.9.1. The volume of the n-dimensional unit ball -- 27.2.10. The m-dimensional Hausdorff measure -- 27.2.11. Jordan sets -- 27.3. Main approaches for IPA -- 27.3.1. Rectifiable objects -- 27.3.1.1. Besicovitch-Federer's decomposition theorem -- 27.3.2. Parallel dilated objects -- 27.3.3. The Minkowski contents -- 27.3.3.1. The m-dimensional Minkowski content -- 27.3.3.2. The outer and two-sided n-dimensional Minkowski content -- 27.3.4. The Fréchet-Nikodym-Aronszajn distance -- 27.3.5. Caccioppoli sets -- 27.4. Applications to IPA -- 27.4.1. Perimeter measures -- 27.4.1.1. The Minkowski-Steiner's formula -- 27.4.1.2. Caccioppoli-De Giorgi's perimeter -- 27.4.2. Invariant measures -- 27.4.2.1. Haar measures -- 27.4.3. The m-dimensional Favard measure -- 27.4.3.1. Purely unrectifiable sets.

27.4.4. Comparison of objects -- 27.5. Additional comments -- Historical comments and references -- Bibliographic notes and additional readings -- Further topics and readings -- Some references on applications to IPA -- Chapter 28: The Integral Geometric Framework -- 28.1. Paradigms -- 28.2. Mathematical concepts and structures -- 28.2.1. Mathematical disciplines -- 28.2.2. Geometric functionals -- 28.2.3. Intrinsic volumes and Minkowski functionals on compact convex objects -- 28.2.3.1. The Steiner polynomials -- 28.2.3.2. Properties of intrinsic volumes and Minkowski functionals -- 28.2.4. Content functionals on finite unions of compact convex objects -- 28.2.4.1. Properties of Minkowski functionals -- 28.2.5. Hadwiger's characterization theorem -- 28.2.6. Particular m-dimensional content functionals -- 28.2.6.1. Integral of mean curvature and mean breadth for compact convex objects -- 28.2.7. Continuity of geometric functionals -- 28.3. Main approaches for IPA -- 28.3.1. The Favard measure and Cauchy-Crofton's formulas -- 28.3.2. Cauchy-Crofton's formulas for compact, poly-convex objects -- 28.3.3. Cauchy-Crofton's formulas for a k-dimensional countably rectifiable manifold -- 28.3.4. Intersections with lower dimensional affine subspaces -- 28.3.5. The covariogram of a measurable object -- 28.3.5.1. Lipschitzian covariograms -- 28.4. Applications to IPA -- 28.4.1. p-dimensional affine sections -- 28.4.2. m-dimensional content functionals for n=1, 2 and 3 -- 28.4.3. Steiner's formulas for n=1, 2 and 3 -- 28.4.4. Cauchy-Crofton's formulas in dimension 2 and 3 -- 28.4.4.1. Cauchy-Crofton's formulas in dimension 3 -- 28.4.4.2. Cauchy-Crofton's formulas in dimension 2 -- 28.4.5. Feret diameters and areas -- 28.4.6. Other diameters -- 28.4.7. Cauchy's projection formulas -- 28.4.7.1. Cauchy's projection formula for convex bodies.

28.4.7.2. Cauchy's total projection formulae for curve length.
Abstract:
Mathematical Imaging is currently a rapidly growing field in applied mathematics, with an increasing need for theoretical mathematics. This book, the second of two volumes, emphasizes the role of mathematics as a rigorous basis for imaging sciences. It provides a comprehensive and convenient overview of the key mathematical concepts, notions, tools and frameworks involved in the various fields of gray-tone and binary image processing and analysis, by proposing a large, but coherent, set of symbols and notations, a complete list of subjects and a detailed bibliography. It establishes a bridge between the pure and applied mathematical disciplines, and the processing and analysis of gray-tone and binary images. It is accessible to readers who have neither extensive mathematical training, nor peer knowledge in Image Processing and Analysis. It is a self-contained book focusing on the mathematical notions, concepts, operations, structures, and frameworks that are beyond or involved in Image Processing and Analysis. The notations are simplified as far as possible in order to be more explicative and consistent throughout the book and the mathematical aspects are systematically discussed in the image processing and analysis context, through practical examples or concrete illustrations. Conversely, the discussed applicative issues allow the role of mathematics to be highlighted. Written for a broad audience - students, mathematicians, image processing and analysis specialists, as well as other scientists and practitioners - the author hopes that readers will find their own way of using the book, thus providing a mathematical companion that can help mathematicians become more familiar with image processing and analysis, and likewise, image processing and image analysis scientists, researchers and engineers gain a deeper understanding of mathematical

notions and concepts.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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