Three-dimensional interpretation of an imperfect line drawing.

by Leung Kin Lap.Thesis (M.Phil.)--Chinese University of Hong Kong, 1996.Includes bibliographical references (leaves 70-72).ACKNOWLEDGEMENTS --- p.IABSTRACT --- p.IITABLE OF CONTENTS --- p.IIITABLE OF FIGURES --- p.IVChapter Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Contributions of the thesis --- p.2Chapter 1.2 --- Organization of the thesis --- p.4Chapter Chapter 2 --- Previous Work --- p.5Chapter 2.1 --- An overview of 3-D interpretation --- p.5Chapter 2.1.1 --- Multiple-View Clues --- p.5Chapter 2.1.2 --- Single-View Clues --- p.6Chapter 2.2 --- Line Drawing Interpretation --- p.7Chapter 2.2.1 --- Qualitative Interpretation --- p.7Chapter 2.2.2 --- Quantitative Interpretation --- p.10Chapter 2.3 --- Previous Methods of Quantitative Interpretation by Optimization --- p.12Chapter 2.3.1 --- Extremum Principle for Shape from Contour --- p.12Chapter 2.3.2 --- MSDA Algorithm --- p.14Chapter 2.4 --- Comments on Previous Work on Line Drawing Interpretation --- p.17Chapter Chapter 3 --- An Iterative Clustering Procedure for Imperfect Line Drawings --- p.18Chapter 3.1 --- Shape Constraints --- p.19Chapter 3.2 --- Problem Formulation --- p.20Chapter 3.3 --- Solution Steps --- p.25Chapter 3.4 --- Nearest-Neighbor Clustering Algorithm --- p.37Chapter 3.5 --- Discussion --- p.38Chapter Chapter 4 --- Experimental Results --- p.40Chapter 4.1 --- Synthetic Line Drawings --- p.40Chapter 4.2 --- Real Line Drawing --- p.42Chapter 4.2.1 --- Recovery of real images --- p.42Chapter Chapter 5 --- Conclusion and Future Work --- p.65Appendix A --- p.67Chapter A. 1 --- Gradient Space Concept --- p.67Chapter A. 2 --- Shading of images --- p.69Appendix B --- p.7

Statistical methods for polyhedral shape classification with incomplete data - application to cryo-electron tomographic images

A certain type of bacterial inclusion, known as a bacterial microcompartment, was recently identified and imaged through cryo-electron tomography. A reconstructed 3D object from single-axis limited angle tilt-series cryo-electron tomography contains missing regions and this problem is known as the missing wedge problem. Due to missing regions on the reconstructed images, analyzing their 3D structures is a challenging problem. The existing methods overcome this problem by aligning and averaging several similar shaped objects. These schemes work well if the objects are symmetric and several objects with almost similar shapes and sizes are available. Since the bacterial inclusions studied here are not symmetric, are deformed, and show a wide range of shapes and sizes, the existing approaches are not appropriate. This research develops new statistical methods for analyzing geometric properties, such as volume, symmetry, aspect ratio, polyhedral structures etc., of these bacterial inclusions in presence of missing data. These methods work with deformed and non-symmetric varied shaped objects and do not necessitate multiple objects for handling the missing wedge problem. The developed methods and contributions include: (a) an improved method for manual image segmentation, (b) a new approach to 'complete' the segmented and reconstructed incomplete 3D images, (c) a polyhedral structural distance model to predict the polyhedral shapes of these microstructures, (d) a new shape descriptor for polyhedral shapes, named as polyhedron profile statistic, and (e) the Bayes classifier, linear discriminant analysis and support vector machine based classifiers for supervised incomplete polyhedral shape classification. Finally, the predicted 3D shapes for these bacterial microstructures belong to the Johnson solids family, and these shapes along with their other geometric properties are important for better understanding of their chemical and biological characteristics