臺灣博碩士論文加值系統

本文針對距離影像的擷取, 以及低階、中階、乃至於高階的處理,作了一
系列的探討和研究。在距離影像的擷取方面,我們提出了利用雷射或彩色
條紋光源配合立體視覺的兩種方法。在低階處理方面,我們提出了一個利
用時變的數學形態學對距離影像作平滑處理的架構。接著,在中階處理方
面,我們利用數學形態學抽取具不變性的影像特徵。最後,在高階處理方
面,我們利用所抽取出的特徵,配合幾何雜湊法來從事三維物體辨認的工作
。

In this thesis, a complete study from the low-level to the high-
level processing of range images has been made. First, two
active-stereo approaches were developed for range image
acquisition. In low-level processing, spatially- variant
morphology was used for range images smoothing. In middle-level
processing, invariant features were extracted using
mathematical morphology. In high-level processing, a method
which combines morphological feature extraction and geometric
hashing was developed for 3D object recognition.

Cover
Range Image Processing Using Mathematical Morphology and Its Application on 3D Object Recognition
Contents
Chpater 1 Introduction
1.1 Backgrounds and Motivations
1.2 Organization of This Thesis
1.3 Contributions of This Thesis
Part 1 Range Data Acqusition Using Active Lighting and Stereo Vision
Chapter 2 3D Range Data Acquisition Combining Laser Lighting and Stereo Vision
2.1 Introduction
2.2 3D Range Data Acqusition by the Laser-Stereo Range Finder
2.3 Light Stripe Extraction and Matching
2.4 Accuracy Tests
2.5 Experimental Results
2.6 Conclusding Remarks
Chapter 3 Range Data Acquisition Using Color Structured Lighting jand Stereo Vision
3.1 Introduction
3.2 Generation of Color Structured Pattern
3.3 Stereo Matching Using Intra-Scanline Search and Inter-Scanline Consistency
3.4 Experimental Results
3.5 Concluding Remarks
Part 2 Adaptive Smoothing of Range Images Using S[atially-Variant Morphological Operators
Chapter 4 Theoretical Aspects of the Vertically-Invariant Gray-Level Morphological
Operators and Their Applications on Adaptive Filtering of Range Images
4.1 Introduction
4.2 Morphological V-Operators
4.3 Using Morphological V-Operators for Adaptive Signal Filltering
4.4 Experimental Results
4.5 Concluding Remarks
Cjhapter 5 Statistical Analysis of the Morphological Vertically-Invariant Openings with
Flat Structuring Elements
5.1 Introduction
5.2 Statistical Analysis of MV-Openings with Flat Structuring Eklements
5.3 Statistical Analysis of the Filtering Result of a Noisy Edge Model
5.4 Concluding Remarks
Part 3 Invariant Feature Extraction
Chapter 6 Invariant Feature Extraction form Range Images Using Mathematical Morphology
6.1 Introduction
6.2 Orthogonal Residue
6.3 Skeleton of the High-Variation Region
6.4 Experimental Results
6.5 Concluding Remarks
jPart 4 3D Object Recognition
Chapter 7 Three-Dimensional Object Recognition with Range Images by Combining
Morphological Feature Extraction and Gemetric Hashing
7.1 Introduction
7.2 Low-Level Processing and Feature Extraction of Range Images
7.3 Geometric Hashing for 3D Object Recognition
7.4 Experimental Results
7.5 Concluding Remarks
Chapter 8 Conclusions and Future Work
References