Multi-scale numerical simulation: the applications in face recognition and micro- electro- mechanical systems
Date Issued
2006
Date
2006
Author(s)
Lin, Tzung-Han
DOI
en-US
Abstract
This dissertation presents multi-scale numerical simulations in four categories. They are face recognition/authentication, smoothing medical models, assessment of sphericity and dissipative particle dynamics simulations. In chapter 2, we present a novel method for automatic face authentication in which the variance of faces due to aging has been considered. A bilateral symmetrical plane is used for weighting the correspondences of the scanned model and database model upon model verification. This bilateral symmetrical plane is determined by the nose tip and two canthus features. The coupled 2D and 3D feature-extraction method is introduced to determine the positions of these canthus features. The central profile on this bilateral symmetrical plane is the foundation of the face recognition. A weighting function is used to determine the rational points for the correspondences of the optimized iterative closest point method. The discrepancy value is evaluated for the authentication and compensation between different models. We have implemented this method on the practical authentication of human faces. The result illustrates that this method works well in both self authentication and mutual authentication. The third chapter aims to present a method of smoothing medical STL models by linear blending. Marching cubes is a popular tool for constructing 3-D STL models from DICOM medical images. However, extra high curvatures and topological problems are the possible defects in STL models formed by marching cubes. Hence, some of the STL models are inapplicable. An octree data structure is used for avoiding redundant vertices of connected triangular facets for a STL model. The blending concept is induced for blending one point on STL models with its neighboring points to smooth the surface. It is also used to improve the surface quality of medical STL models. The compensation of the volume is also introduced to avoid shrinkage caused by smoothing iterations. In each iteration, this smoothing method processes in linear time. A constant blending factor and a variable blending factor associated with curvatures are applied for different smoothing goals. In chapter 4, we present a numerical method for the sphericity assessment of the pellet in micro/nano scale. The numerical method based on Newton’s method is used for solving the least square problem. In one SEM image, the minimum root mean square (RMS) circle is determined from the observed pellet. The sphericity assessment of the pellet needs at least two SEM images which are captured from different views. The measured points on each captured image are acquired by twice linear interpolations of sub-pixels which are located on the boundary of the observed pellet. Once these minimum RMS circles have been determined, the corresponding homogenous transformations are applied to all measured points in order to restore the 3D points. The normalized 3D points represent the observed pellet properly, and they are the foundation for sphericity assessment. In chapter 5, we present a three-dimensional dissipative particle dynamics simulation, which is independent of the initial conditions, for analyzing the wettability on liquid-solid interfaces. The model parameters are constructed based on simulation optimization. The contact angle of a droplet on the solid platforms which possess different surface energy is simulated. The normalized factors indicate the parameters of the surface energy. By tuning the attractive and repulsive effects between the platform and the droplet, the contact angles with wide range are found at steady states. In simulation result, the linear relation between contact angle and the normalized factor exists. The proper repulsive factor in the paper is recommended to from 15 to 20. The ranges of the contact angles are from about 55 to 165 degrees. Moreover, the local density and the equation of state are applied for determining the droplet's self energy and compressibility. The simulation results will help us to predict the profile and internal physical behavior of a micro-droplet.
Subjects
人臉辨識
特徵萃取
平滑化
混合
真球度
微系統量測
微機電系統
耗散性分子動力學
Face recognition
feature detection
Smoothing
Blending
Marching cubes
Sphericity
Micro-coordinate measurement
Dissipative particles dynamics
Type
thesis
File(s)![Thumbnail Image]()
Loading...
Name
ntu-95-D88522005-1.pdf
Size
23.53 KB
Format
Adobe PDF
Checksum
(MD5):bbb120ded64a165d3aedb058f10d4ecc