Various fields of image analysis, computer vision, and artificial intelligence require a description of shape in grey-level images, but the automatic performance of these tasks can only succeed if a suitable description of shape is available. This book presents a comprehensive overview of the mathematical description of shape from the viewpoint of a broad range of disciplines. The emphasis is on the methodology and the underlying mathematics. The concept of shape is explored in terms of such disciplines as digital topology and geometry, categorial shape theory, mathematical morphology, wavelets, differential geometry, graph and hierarchical representation methods, and evolutionary systems.
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First Sentence:
In principle, shape is that quality of an object that depends on the relative positions of all the points comprising its outline or external surface. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
categorical shape theory, affine equivalence problem, harmonic polygon, polygonal harmonics, digital homotopy, foldable figure, curve pyramid, convex subparts, umbra transform, surviving vertices, quadratic structuring functions, erosion curve, interrelation symbols, relative affine invariants, diagonal growth, fuzzy proximity, regular tempered distribution, connected structuring elements, initial subcategory, fuzzy proximities, visual manifold, quench function, cortical retina, fuzzy locations, probabilistic mixing Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Academic Press, Artificial Intelligence, Haar Romeny, Pattern Anal, Department of Computer Science, Cambridge University Press, Mac Lane, Machine Intell, Marcel Dekker, John Wiley, Joint Conf, Royal Institute of Technology, College Park, New Jersey, The Netherlands Abstract, Mean Std, San Diego, Springer Verlag, University of Maryland, Akademie Verlag, International Conference, Lecture Notes, Machine Learning, North Carolina New!
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In principle, shape is that quality of an object that depends on the relative positions of all the points comprising its outline or external surface. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
categorical shape theory, affine equivalence problem, harmonic polygon, polygonal harmonics, digital homotopy, foldable figure, curve pyramid, convex subparts, umbra transform, surviving vertices, quadratic structuring functions, erosion curve, interrelation symbols, relative affine invariants, diagonal growth, fuzzy proximity, regular tempered distribution, connected structuring elements, initial subcategory, fuzzy proximities, visual manifold, quench function, cortical retina, fuzzy locations, probabilistic mixing Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Academic Press, Artificial Intelligence, Haar Romeny, Pattern Anal, Department of Computer Science, Cambridge University Press, Mac Lane, Machine Intell, Marcel Dekker, John Wiley, Joint Conf, Royal Institute of Technology, College Park, New Jersey, The Netherlands Abstract, Mean Std, San Diego, Springer Verlag, University of Maryland, Akademie Verlag, International Conference, Lecture Notes, Machine Learning, North Carolina New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 100
books:
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2
books
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- Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning (Proceedings of Spie) by Edward R. Dougherty on 5 pages
- Random Sets and Integral Geometry (Probability & Mathematical Statistics) by F. Matheron on 5 pages
- Mathematical Morphology in Image Processing (Optical Science and Engineering) by Edward Dougherty on 5 pages
- Mathematical Morphology by John Goutsias on 4 pages
- Structural Pattern Recognition (Springer Series in Electrophysics) by T. Pavlidis on page 36, page 558, and Back Matter
See all 100 books this book cites
- Image Analysis: Methods and Applications, Second Edition by Donat P. Hader on page 64
- Geometry of Digital Spaces (Applied and Numerical Harmonic Analysis) by Gabor T. Herman in Back Matter
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