Gauch Multiresolution Image Shape Description

1992
ISBN: 978-1-4612-2832-5
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 131 Seiten, eBook

Reihe: Springer Series in Perception Engineering

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.

Zielgruppe

Research

Autoren/Hrsg.

Gauch, John M.

Inhaltsverzeichnis

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.- 2.3.1. Axis Topology.- 2.3.2. Axis Bending and Branching.- 2.3.3. Axis Radius Function.- 2.3.4. Axis Inverse Mapping.- 2.3.5. Axis Invariance.- 2.4. Discussion.- 3 Computing the Intensity Axis of Symmetry.- 3.1. Level by Level Calculation of Axes.- 3.2. Simultaneous Calculation of Axes.- 3.2.1. A Review of the Active Contour Model.- 3.2.2. The Active Surface Model.- 3.2.3. The Image Symmetry Function.- 3.2.4. Linking the Active Surface.- 3.2.5. Identifying Individual Axis Sheets.- 3.2.6. Calculating the Radius and Curvature Functions.- 3.3. Discussion.- 4 Segmentation via the Intensity Axis of Symmetry.- 4.1. Displaying the IAS.- 4.2. Image Segmentation.- 4.2.1. Segmentation Method.- 4.2.2. Segmentation Results.- 4.3. Effects of Image Processing.- 4.3.1. Contrast Enhancement.- 4.3.2. Gaussian Blurring.- 4.3.3. Edge Strength Images.- 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.- 5.3.1. Boundary Curvature and Vertices.- 5.3.2. Surface Curvature.- 5.3.3. Level Curve Curvature and Vertex Curves.- 5.3.4. Vertex Curve Topology.- 5.3.5. Multiresolution Properties of Vertex Curves.- 5.4. Multiresolution Watershed Boundaries.- 5.4.1. Watersheds and Their Boundaries.- 5.4.2. Linking Intensity Extrema.- 5.4.3. Displaying Watershed Region Hierarchies.- 5.4.4. Associating Scale with Watershed Boundaries.- 5.4.5. Imposing a Quasi-Hierarchy on IAS Sheets.- 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.