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3D image segmentation. / Three-dimensional image segmentation

Wai-kin Vong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 87-[91]). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Three Dimensional Image --- p.1 / Chapter 1.2 --- Definition of segmentation --- p.2 / Chapter 1.3 --- 3D Image Segmentation --- p.3 / Chapter 1.4 --- Image Splitting Operation --- p.4 / Chapter 1.5 --- Region Merging Operation --- p.4 / Chapter 1.6 --- Split-and-merge Segmentation --- p.4 / Chapter 1.6.1 --- Selection of particular operators --- p.5 / Chapter 2 --- Overview of Image Segmentation Techniques --- p.6 / Chapter 2.1 --- Introduction --- p.6 / Chapter 2.2 --- Edge Based Method --- p.6 / Chapter 2.2.1 --- 3D Laplacian of Gaussian Filtering --- p.7 / Chapter 2.2.2 --- 3D Deformable Surfaces [8] --- p.11 / Chapter 2.3 --- Region Based Method --- p.14 / Chapter 2.3.1 --- 3D oct-tree split-and-merge --- p.15 / Chapter 2.3.2 --- 3D pyramid segmentation --- p.17 / Chapter 2.4 --- 2D segmentation Approaches --- p.20 / Chapter 2.4.1 --- 2D Image segmentation by shape description --- p.20 / Chapter 2.4.2 --- Morphological Watershed Transform (WT) --- p.23 / Chapter 2.5 --- Discussion --- p.34 / Chapter 3 --- Modification Of Digital Watershed Transform (DWT) --- p.36 / Chapter 3.1 --- Introduction --- p.36 / Chapter 3.2 --- Edge Detection --- p.37 / Chapter 3.2.1 --- Discrete Non-linear Edge Detectors --- p.37 / Chapter 3.2.2 --- Canny's Edge Detector --- p.40 / Chapter 3.2.3 --- Gradient of Gaussian Filter --- p.42 / Chapter 3.3 --- Digital Watershed Transform --- p.46 / Chapter 3.3.1 --- Introduction --- p.46 / Chapter 3.3.2 --- Modification of SKIZ --- p.46 / Chapter 3.3.3 --- Implementation --- p.51 / Chapter 4 --- Region Modeling --- p.55 / Chapter 4.1 --- Introduction --- p.55 / Chapter 4.2 --- Texture Definition --- p.57 / Chapter 4.3 --- Texture Modeling --- p.58 / Chapter 4.3.1 --- Markov Random Field (MRF) --- p.58 / Chapter 4.3.2 --- Simultaneous Autoregressive (SAR) Model --- p.59 / Chapter 4.3.3 --- Parameter Estimation --- p.61 / Chapter 4.3.4 --- A Simple model --- p.63 / Chapter 4.3.5 --- Combination of MRF parameters --- p.63 / Chapter 4.3.6 --- Similarity Measure --- p.66 / Chapter 4.4 --- Model Evaluation --- p.68 / Chapter 4.4.1 --- Classification of Different Materials --- p.68 / Chapter 4.4.2 --- Rotational Invariance --- p.69 / Chapter 4.5 --- Results and Observations --- p.72 / Chapter 5 --- Three-Dimensional Segmentation with Interactive Labeling --- p.73 / Chapter 5.1 --- Introduction --- p.73 / Chapter 5.2 --- Region Merging Scheme --- p.75 / Chapter 5.3 --- Interactive Labeling --- p.76 / Chapter 5.4 --- Experiment of 3D Guided Segmentation --- p.77 / Chapter 6 --- Conclusion --- p.81 / Chapter 6.1 --- Image Partitioning by Watershed Transform --- p.81 / Chapter 6.2 --- Image modeling by Markov Random Field --- p.82 / Chapter 6.3 --- 3D image segmentation --- p.82 / A --- p.84 / B --- p.86 / Bibliography --- p.87

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_318212
Date January 1994
ContributorsVong, Wai-kin., Chinese University of Hong Kong Graduate School. Division of Information Engineering.
PublisherChinese University of Hong Kong
Source SetsThe Chinese University of Hong Kong
LanguageEnglish
Detected LanguageEnglish
TypeText, bibliography
Formatprint, vi, 87, [4] leaves : ill. (some mounted ill.) ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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