2D and 3D Image Analysis by Moments. (Record no. 121987)
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| fixed length control field | 11140nam a22005173i 4500 |
| 001 - CONTROL NUMBER | |
| control field | EBC4786294 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | MiAaPQ |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240729131032.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS | |
| fixed length control field | m o d | |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr cnu|||||||| |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240724s2016 xx o ||||0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781119039372 |
| Qualifying information | (electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| Canceled/invalid ISBN | 9781119039358 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (MiAaPQ)EBC4786294 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (Au-PeEL)EBL4786294 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (CaPaEBR)ebr11330537 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (CaONFJC)MIL971739 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | (OCoLC)962052083 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | MiAaPQ |
| Language of cataloging | eng |
| Description conventions | rda |
| -- | pn |
| Transcribing agency | MiAaPQ |
| Modifying agency | MiAaPQ |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | TA1637.F587 2017 |
| 082 0# - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 621.367015159 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Flusser, Jan. |
| 245 10 - TITLE STATEMENT | |
| Title | 2D and 3D Image Analysis by Moments. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Newark : |
| Name of producer, publisher, distributor, manufacturer | John Wiley & Sons, Incorporated, |
| Date of production, publication, distribution, manufacture, or copyright notice | 2016. |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Date of production, publication, distribution, manufacture, or copyright notice | ©2017. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 1 online resource (556 pages) |
| 336 ## - CONTENT TYPE | |
| Content type term | text |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type term | computer |
| Media type code | c |
| Source | rdamedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | online resource |
| Carrier type code | cr |
| Source | rdacarrier |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Cover -- Title Page -- Copyright -- Dedication -- Contents -- Preface -- Acknowledgements -- Chapter 1 Motivation -- 1.1 Image analysis by computers -- 1.2 Humans, computers, and object recognition -- 1.3 Outline of the book -- References -- Chapter 2 Introduction to Object Recognition -- 2.1 Feature space -- 2.1.1 Metric spaces and norms -- 2.1.2 Equivalence and partition -- 2.1.3 Invariants -- 2.1.4 Covariants -- 2.1.5 Invariant-less approaches -- 2.2 Categories of the invariants -- 2.2.1 Simple shape features -- 2.2.2 Complete visual features -- 2.2.3 Transformation coefficient features -- 2.2.4 Textural features -- 2.2.5 Wavelet-based features -- 2.2.6 Differential invariants -- 2.2.7 Point set invariants -- 2.2.8 Moment invariants -- 2.3 Classifiers -- 2.3.1 Nearest-neighbor classifiers -- 2.3.2 Support vector machines -- 2.3.3 Neural network classifiers -- 2.3.4 Bayesian classifier -- 2.3.5 Decision trees -- 2.3.6 Unsupervised classification -- 2.4 Performance of the classifiers -- 2.4.1 Measuring the classifier performance -- 2.4.2 Fusing classifiers -- 2.4.3 Reduction of the feature space dimensionality -- 2.5 Conclusion -- References -- Chapter 3 2D Moment Invariants to Translation, Rotation, and Scaling -- 3.1 Introduction -- 3.1.1 Mathematical preliminaries -- 3.1.2 Moments -- 3.1.3 Geometric moments in 2D -- 3.1.4 Other moments -- 3.2 TRS invariants from geometric moments -- 3.2.1 Invariants to translation -- 3.2.2 Invariants to uniform scaling -- 3.2.3 Invariants to non-uniform scaling -- 3.2.4 Traditional invariants to rotation -- 3.3 Rotation invariants using circular moments -- 3.4 Rotation invariants from complex moments -- 3.4.1 Complex moments -- 3.4.2 Construction of rotation invariants -- 3.4.3 Construction of the basis -- 3.4.4 Basis of the invariants of the second and third orders -- 3.4.5 Relationship to the Hu invariants. |
| 505 8# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 3.5 Pseudoinvariants -- 3.6 Combined invariants to TRS and contrast stretching -- 3.7 Rotation invariants for recognition of symmetric objects -- 3.7.1 Logo recognition -- 3.7.2 Recognition of shapes with different fold numbers -- 3.7.3 Experiment with a baby toy -- 3.8 Rotation invariants via image normalization -- 3.9 Moment invariants of vector fields -- 3.10 Conclusion -- References -- Chapter 4 3D Moment Invariants to Translation, Rotation, and Scaling -- 4.1 Introduction -- 4.2 Mathematical description of the 3D rotation -- 4.3 Translation and scaling invariance of 3D geometric moments -- 4.4 3D rotation invariants by means of tensors -- 4.4.1 Tensors -- 4.4.2 Rotation invariants -- 4.4.3 Graph representation of the invariants -- 4.4.4 The number of the independent invariants -- 4.4.5 Possible dependencies among the invariants -- 4.4.6 Automatic generation of the invariants by the tensor method -- 4.5 Rotation invariants from 3D complex moments -- 4.5.1 Translation and scaling invariance of 3D complex moments -- 4.5.2 Invariants to rotation by means of the group representation theory -- 4.5.3 Construction of the rotation invariants -- 4.5.4 Automated generation of the invariants -- 4.5.5 Elimination of the reducible invariants -- 4.5.6 The irreducible invariants -- 4.6 3D translation, rotation, and scale invariants via normalization -- 4.6.1 Rotation normalization by geometric moments -- 4.6.2 Rotation normalization by complex moments -- 4.7 Invariants of symmetric objects -- 4.7.1 Rotation and reflection symmetry in 3D -- 4.7.2 The influence of symmetry on 3D complex moments -- 4.7.3 Dependencies among the invariants due to symmetry -- 4.8 Invariants of 3D vector fields -- 4.9 Numerical experiments -- 4.9.1 Implementation details -- 4.9.2 Experiment with archeological findings -- 4.9.3 Recognition of generic classes. |
| 505 8# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 4.9.4 Submarine recognition - robustness to noise test -- 4.9.5 Teddy bears - the experiment on real data -- 4.9.6 Artificial symmetric bodies -- 4.9.7 Symmetric objects from the Princeton Shape Benchmark -- 4.10 Conclusion -- Appendix 4.A -- Appendix 4.B -- Appendix 4.C -- References -- Chapter 5 Affine Moment Invariants in 2D and 3D -- 5.1 Introduction -- 5.1.1 2D projective imaging of 3D world -- 5.1.2 Projective moment invariants -- 5.1.3 Affine transformation -- 5.1.4 2D Affine moment invariants-the history -- 5.2 AMIs derived from the Fundamental theorem -- 5.3 AMIs generated by graphs -- 5.3.1 The basic concept -- 5.3.2 Representing the AMIs by graphs -- 5.3.3 Automatic generation of the invariants by the graph method -- 5.3.4 Independence of the AMIs -- 5.3.5 The AMIs and tensors -- 5.4 AMIs via image normalization -- 5.4.1 Decomposition of the affine transformation -- 5.4.2 Relation between the normalized moments and the AMIs -- 5.4.3 Violation of stability -- 5.4.4 Affine invariants via half normalization -- 5.4.5 Affine invariants from complex moments -- 5.5 The method of the transvectants -- 5.6 Derivation of the AMIs from the Cayley-Aronhold equation -- 5.6.1 Manual solution -- 5.6.2 Automatic solution -- 5.7 Numerical experiments -- 5.7.1 Invariance and robustness of the AMIs -- 5.7.2 Digit recognition -- 5.7.3 Recognition of symmetric patterns -- 5.7.4 The children's mosaic -- 5.7.5 Scrabble tiles recognition -- 5.8 Affine invariants of color images -- 5.8.1 Recognition of color pictures -- 5.9 Affine invariants of 2D vector fields -- 5.10 3D affine moment invariants -- 5.10.1 The method of geometric primitives -- 5.10.2 Normalized moments in 3D -- 5.10.3 Cayley-Aronhold equation in 3D -- 5.11 Beyond invariants -- 5.11.1 Invariant distance measure between images -- 5.11.2 Moment matching. |
| 505 8# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 5.11.3 Object recognition as a minimization problem -- 5.11.4 Numerical experiments -- 5.12 Conclusion -- Appendix 5.A -- Appendix 5.B -- References -- Chapter 6 Invariants to Image Blurring -- 6.1 Introduction -- 6.1.1 Image blurring-the sources and modeling -- 6.1.2 The need for blur invariants -- 6.1.3 State of the art of blur invariants -- 6.1.4 The chapter outline -- 6.2 An intuitive approach to blur invariants -- 6.3 Projection operators and blur invariants in Fourier domain -- 6.4 Blur invariants from image moments -- 6.5 Invariants to centrosymmetric blur -- 6.6 Invariants to circular blur -- 6.7 Invariants to N-FRS blur -- 6.8 Invariants to dihedral blur -- 6.9 Invariants to directional blur -- 6.10 Invariants to Gaussian blur -- 6.10.1 1D Gaussian blur invariants -- 6.10.2 Multidimensional Gaussian blur invariants -- 6.10.3 2D Gaussian blur invariants from complex moments -- 6.11 Invariants to other blurs -- 6.12 Combined invariants to blur and spatial transformations -- 6.12.1 Invariants to blur and rotation -- 6.12.2 Invariants to blur and affine transformation -- 6.13 Computational issues -- 6.14 Experiments with blur invariants -- 6.14.1 A simple test of blur invariance property -- 6.14.2 Template matching in satellite images -- 6.14.3 Template matching in outdoor images -- 6.14.4 Template matching in astronomical images -- 6.14.5 Face recognition on blurred and noisy photographs -- 6.14.6 Traffic sign recognition -- 6.15 Conclusion -- Appendix 6.A -- Appendix 6.B -- Appendix 6.C -- Appendix 6.D -- Appendix 6.E -- Appendix 6.F -- Appendix 6.G -- References -- Chapter 7 2D and 3D Orthogonal Moments -- 7.1 Introduction -- 7.2 2D moments orthogonal on a square -- 7.2.1 Hypergeometric functions -- 7.2.2 Legendre moments -- 7.2.3 Chebyshev moments -- 7.2.4 Gaussian-Hermite moments -- 7.2.5 Other moments orthogonal on a square. |
| 505 8# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 7.2.6 Orthogonal moments of a discrete variable -- 7.2.7 Rotation invariants from moments orthogonal on a square -- 7.3 2D moments orthogonal on a disk -- 7.3.1 Zernike and Pseudo-Zernike moments -- 7.3.2 Fourier-Mellin moments -- 7.3.3 Other moments orthogonal on a disk -- 7.4 Object recognition by Zernike moments -- 7.5 Image reconstruction from moments -- 7.5.1 Reconstruction by direct calculation -- 7.5.2 Reconstruction in the Fourier domain -- 7.5.3 Reconstruction from orthogonal moments -- 7.5.4 Reconstruction from noisy data -- 7.5.5 Numerical experiments with a reconstruction from OG moments -- 7.6 3D orthogonal moments -- 7.6.1 3D moments orthogonal on a cube -- 7.6.2 3D moments orthogonal on a sphere -- 7.6.3 3D moments orthogonal on a cylinder -- 7.6.4 Object recognition of 3D objects by orthogonal moments -- 7.6.5 Object reconstruction from 3D moments -- 7.7 Conclusion -- References -- Chapter 8 Algorithms for Moment Computation -- 8.1 Introduction -- 8.2 Digital image and its moments -- 8.2.1 Digital image -- 8.2.2 Discrete moments -- 8.3 Moments of binary images -- 8.3.1 Moments of a rectangle -- 8.3.2 Moments of a general-shaped binary object -- 8.4 Boundary-based methods for binary images -- 8.4.1 The methods based on Green's theorem -- 8.4.2 The methods based on boundary approximations -- 8.4.3 Boundary-based methods for 3D objects -- 8.5 Decomposition methods for binary images -- 8.5.1 The "delta" method -- 8.5.2 Quadtree decomposition -- 8.5.3 Morphological decomposition -- 8.5.4 Graph-based decomposition -- 8.5.5 Computing binary OG moments by means of decomposition methods -- 8.5.6 Experimental comparison of decomposition methods -- 8.5.7 3D decomposition methods -- 8.6 Geometric moments of graylevel images -- 8.6.1 Intensity slicing -- 8.6.2 Bit slicing -- 8.6.3 Approximation methods -- 8.7 Orthogonal moments of graylevel images. |
| 505 8# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 8.7.1 Recurrent relations for moments orthogonal on a square. |
| 588 ## - SOURCE OF DESCRIPTION NOTE | |
| Source of description note | Description based on publisher supplied metadata and other sources. |
| 590 ## - LOCAL NOTE (RLIN) | |
| Local note | Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Image analysis. |
| 655 #4 - INDEX TERM--GENRE/FORM | |
| Genre/form data or focus term | Electronic books. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Suk, Tomas. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Zitova, Barbara. |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Print version: |
| Main entry heading | Flusser, Jan |
| Title | 2D and 3D Image Analysis by Moments |
| Place, publisher, and date of publication | Newark : John Wiley & Sons, Incorporated,c2016 |
| International Standard Book Number | 9781119039358 |
| 797 2# - LOCAL ADDED ENTRY--CORPORATE NAME (RLIN) | |
| Corporate name or jurisdiction name as entry element | ProQuest (Firm) |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://ebookcentral.proquest.com/lib/orpp/detail.action?docID=4786294">https://ebookcentral.proquest.com/lib/orpp/detail.action?docID=4786294</a> |
| Public note | Click to View |
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