Multiresolution image shape description
著者
書誌事項
Multiresolution image shape description
（Springer series in perception engineering）
Springer-Verlag, c1992
- : New York
- : Berlin
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注記
Revision of the author's thesis (Ph.D.)--University of North Carolina at Chapel Hill, 1989
Bibliography: p. [119]-126
Includes index
内容説明・目次
- 巻冊次
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: New York ISBN 9780387976822
内容説明
Much of our understanding of the relationships among geometric struc tures in images is based on the shape of these structures and their relative orientations, positions and sizes. Thus, developing quantitative methods for capturing shape information from digital images is an important area for computer vision research. This book describes the theory, implemen tation, and application of two multi resolution image shape description methods. The author begins by motivating the need for quantitative methods for describing both the spatial and intensity variations of struc tures in grey-scale images. Two new methods which capture this informa tion are then developed. The first, the intensity axis of symmetry, is a collection of branching and bending surfaces which correspond to the skeleton of the image. The second method, multiresolution vertex curves, focuses on surface curvature properties as the image is blurred by a sequence of Gaussian filters. Implementation techniques for these image shape descriptions are described in detail. Surface functionals are mini mized subject to symmetry constraints to obtain the intensity axis of symmetry. Robust numerical methods are developed for calculating and following vertex curves through scale space. Finally, the author demon strates how grey-scale images can be segmented into geometrically coher ent regions using these shape description techniques. Building quantita tive analysis applications in terms of these visually sensible image regions promises to be an exciting area of biomedical computer vision research. v Acknowledgments This book is a corrected and revised version of the author's Ph. D.
目次
1 Introduction and Background.- 1.1. Shape Description.- 1.2. Image Description.- 1.3. Image Shape Description.- 2 The Intensity Axis of Symmetry.- 2.1. Axes of Symmetry.- 2.2. The Intensity Axis of Symmetry (IAS).- 2.3. Properties of the IAS.- 2.4. Discussion.- 3 Computing the Intensity Axis of Symmetry.- 3.1. Level by Level Calculation of Axes.- 3.2. Simultaneous Calculation of Axes.- 3.3. Discussion.- 4 Segmentation via the Intensity Axis of Symmetry.- 4.1. Displaying the IAS.- 4.2. Image Segmentation.- 4.3. Effects of Image Processing.- 4.4. Discussion.- 5 Multiresolution Analysis of the Intensity Axis of Symmetry.- 5.1. Early Multiresolution Analysis.- 5.2. The Multiresolution IAS.- 5.3. Multiresolution Vertex Curves.- 5.4. Multiresolution Watershed Boundaries.- 5.5. Discussion.- 6 Conclusions.- 6.1. The Definition of the IAS.- 6.2. An Implementation of the IAS.- 6.3. Image Segmentation Using the IAS.- 6.4. Multiresolution Analysis of the IAS.- 6.5. New Research Directions.
- 巻冊次
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: Berlin ISBN 9783540976820
内容説明
This book addresses one of the central problems in computer-aided image analysis; how the shape of structures in an image should be represented to best facilitate quantitative analysis. To accomplish this task requires an understanding of what shape is and how it should be extracted from grey-scale images. In Professor Gauch's book a new shape description for grey-scale images called the intensity axis of symmetry (IAS) and an associated curvature-based description called vertex curves are presented.
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