Wavelet-based Optimization of Surface Reconstruction

被引:3
|
作者
Kocsis, Peter [1 ]
Balla, Petra [1 ]
Antal, Akos [1 ]
机构
[1] Budapest Univ Technol & Econ, Dept Mechatron Opt & Mech Engn Informat, Muegyet Rkp 3, H-1111 Budapest, Hungary
关键词
profilometry; Wavelet; reconstruction; machine vision; FRINGE-PATTERN ANALYSIS;
D O I
10.12700/APH.15.4.2018.4.10
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
By the development of artificial Intelligence - whether unintentionally - we are constantly trying to mimic the human senses. Biomimicry, as the starting point, is an engineering approach to emulate nature's well working patterns and strategies. Our goal is to create a standalone artificial system which can respond adequately to various environmental impacts without human intervention. In order to detect these influences over the accuracy of human limitations, the most advanced sensors are needed both in software and hardware. The development in computing power highlights some forgotten algorithms, which were neglected because their complexity made them inefficient on early computers. One of these methods is the Wavelet-Transform Profilometry (WTP) of which successful application is demonstrated in this paper. WTP is a three-dimensional profilometric surface reconstruction algorithm in which orthogonal trajectories are used for high-level signal processing of huge datasets. Our goal was to find a high-precision solution for surface reconstruction by replacing the processing software with advanced mathematical methods rather than use more expensive optical systems.
引用
收藏
页码:179 / 198
页数:20
相关论文
共 50 条
  • [31] Wavelet-Based Gaussian Impulse Generation and Optimization for UWB Communication
    Kumar, V. Vinod
    Ajith, V
    Meenakshi, M.
    2015 FIFTH INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING AND COMMUNICATIONS (ICACC), 2015, : 214 - 218
  • [32] A new wavelet-based edge detector via constrained optimization
    Hsieh, JW
    Ko, MT
    Liao, HYM
    Fan, KC
    IMAGE AND VISION COMPUTING, 1997, 15 (07) : 511 - 527
  • [33] Parameter optimization of a wavelet-based electrocardiogram delineator with an evolutionary algorithm
    Dumont, J
    Hernández, AI
    Carrault, G
    COMPUTERS IN CARDIOLOGY 2005, VOL 32, 2005, 32 : 707 - 710
  • [34] Wavelet-based deconvolution
    Novikov, L. V.
    INSTRUMENTS AND EXPERIMENTAL TECHNIQUES, 2007, 50 (01) : 61 - 67
  • [35] Wavelet-Based Multiresolution with
    Lars Linsen
    Bernd Hamann
    Kenneth I. Joy
    Valerio Pascucci
    Mark A. Duchaineau
    Computing, 2004, 72 : 129 - 142
  • [36] Wavelet-based deconvolution
    L. V. Novikov
    Instruments and Experimental Techniques, 2007, 50 : 61 - 67
  • [37] Terahertz computed tomographic reconstruction and its wavelet-based segmentation by fusion
    Yin, X. X.
    Ng, B. W. -H.
    Ferguson, B.
    Mickan, S. P.
    Abbott, D.
    2007 IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS, PROCEEDINGS, VOLS 1-8, 2007, : 3409 - 3414
  • [38] Seismic Data Reconstruction via Wavelet-Based Residual Deep Learning
    Liu, Naihao
    Wu, Lukun
    Wang, Jiale
    Wu, Hao
    Gao, Jinghuai
    Wang, Dehua
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60
  • [39] High performance wavelet-based phase reconstruction of ultrashort laser pulses
    Bethge, Jens
    Steinmeyer, Guenter
    2008 CONFERENCE ON LASERS AND ELECTRO-OPTICS & QUANTUM ELECTRONICS AND LASER SCIENCE CONFERENCE, VOLS 1-9, 2008, : 1047 - 1048
  • [40] Robust Wavelet-Based Super-Resolution Reconstruction: Theory and Algorithm
    Ji, Hui
    Fermueller, Cornelia
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2009, 31 (04) : 649 - 660