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Wavelet-based texture segmentation of titanium based alloy lamellar microstructure: application to images from optical microscope and X-ray microtomography

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Języki publikacji
EN
Abstrakty
EN
A texture segmentation algorithm which combines grey level intensity from 2 images after discrete wavelet transform and variance has been applied on 2D images to segment lamellar colonies in (α+β) titanium alloy Ti6A14V. Images were acquired using both optical microscope and X-ray tomography. The results are satisfying for the former technique and encouraging for the latter one. Possible extension of the method to volumetric data is presented.
Rocznik
Tom
Strony
181--187
Opis fizyczny
Bibliogr. 10 poz.
Twórcy
autor
autor
autor
Bibliografia
  • BABOUT L., MARROW T.J., PREUSS M., (2006), Sequential X-ray Tomography Studies of Damage Assessment in Materials Science, 4th Symposium on Process Tomography in Poland, Warsaw, pp. 159-162.
  • CHEN Z., NING R., (2004), Breast volume denoising and noise characterization by 3D wavelet transform, Computerized Medical Imaging and Graphics, Vol. 28, pp. 235-246.
  • CLOETENS P., PATEYRON-SALOME M., BUFFIERE J.Y., PEIX G., BARUCHEL J., PEYRIN F., SCHLENKER M., (1997), Observation of microstructure and damage in materials by phase sensitive radiography and tomography, Journal of Applied Physics, Vol. 81, pp. 5878-5886.
  • DETTORI L., SEMLER L., (2007), A comparison of wavelet, ridgelet, and curvelet-based texture classification algorithms in computed tomography, Computers in Biology and Medicine, Vol. 37, pp. 486-498.
  • DONOHO D., (2001), Ridge functions and orthonormal ridgelets, Journal of Approximation Theory, Vol. 111, pp. 143-179.
  • HARALICK R.M., SHAPIRO L.G., (1992), Computer and robot vision, Addison-Wesley Publishing Co., Boston, p. 630.
  • KIM S.C., KANG T.J., (2007), Texture classification and segmentation using wavelet packet frame and Gaussian mixture model, Pattern Recognition, Vol. 40, pp. 1207-1221.
  • MALLAT S.G., (1989), A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 11, pp. 674-693.
  • STRZELECKI M., MATERKA A., SZCZYPINSKI P., (2006), MaZda. Texture Analysis for Magnetic Resonance Imaging, Med4publishing, Prague, pp. 105-111.
  • TEUNER A., PICHLER O., HOSTICKA B.J., (1995) Unsupervised texture segmentation of images using tuned matched Gabor filters, Image Processing, IEEE Transactions on, Vol. 4, pp. 863-870.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-LOD1-0020-0046
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