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Model-Based Fatique Fractographs Texture Analysis

  • Michal Haindl
  • Hynek Lauschmann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2396)

Abstract

A novel model-based approach for estimation of the velocity of crack growth from microfractographical images is proposed. These images are represented by a Gaussian Markov random field model and the crack growth rate is modelled by a linear regression model in the Gaussian-Markov parameter space. The method is numerically very efficient because both crack growth rate model parameters as well as the underlying random field model parameters are estimated using fast analytical estimators.

Keywords

Crack Growth Rate Markov Chain Monte Carlo Method Texture Synthesis Markov Random Field Model Crack Growth Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Michal Haindl
    • 1
  • Hynek Lauschmann
    • 2
  1. 1.Institute of Information Theory and AutomationAcademy of Sciences CRPragueCzech Republic
  2. 2.Faculty of Nuclear Science and Physical EngineeringCzech Technical UniversityPragueCzech Republic

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