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Yıl 2010, Cilt: 2 Sayı: 7, 27 - 51, 01.09.2010

Öz

COMPARISON OF DISCRETE WAVELET TRANSFORM AND COMPLEX WAVELET TRANSFORM IN HYBRID SKELETONIZATION BASED ON CVANN

Yıl 2010, Cilt: 2 Sayı: 7, 27 - 51, 01.09.2010

Öz

Curve and surface thinning are widely-used skeletonization techniques
for modeling objects in 3 dimensions. In the case of disordered porous media
analysis, however, neither is really efficient since the internal geometry of the
object is usually composed of both rod and plate shapes. This paper concludes
an application of discrete wavelet transform (WT) and complex wavelet
transform (CWT) in image processing problem such as hybrid skeletonization
of trabecular bone images. Hybrid skeleton combines 2D surfaces and 1D curve
to represent respectively the plate-shaped and rod-shaped parts of the object.
For hybrid skeletonization, two cascade structures are proposed. In these
structures, features of images were extracted with discrete wavelet transform
and complex wavelet transform. After that, obtained features were used as
inputs of complex-valued artificial neural network (CVANN) which is multilayered
artificial neural networks with two dimensions (real and imaginary
parts). Effects of the feature extraction methods are compared for ability of the
hybrid skeletonization on a trabecular bone sample. Results show that the CWT
succeeded to hybrid skeletonization with lower error rate than WT.

Toplam 0 adet kaynakça vardır.

Ayrıntılar

Diğer ID JA53NY59HC
Bölüm Makaleler
Yazarlar

Murat Ceylan Bu kişi benim

Osman Nuri Ucan Bu kişi benim

Yüksel Özbay Bu kişi benim

Rachid Jennane Bu kişi benim

Gabriel Aufort Bu kişi benim

Claude Laurent Benhamou Bu kişi benim

Yayımlanma Tarihi 1 Eylül 2010
Gönderilme Tarihi 1 Eylül 2010
Yayımlandığı Sayı Yıl 2010 Cilt: 2 Sayı: 7

Kaynak Göster

APA Ceylan, M., Ucan, O. N., Özbay, Y., Jennane, R., vd. (2010). COMPARISON OF DISCRETE WAVELET TRANSFORM AND COMPLEX WAVELET TRANSFORM IN HYBRID SKELETONIZATION BASED ON CVANN. İstanbul Aydın Üniversitesi Dergisi, 2(7), 27-51.


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