The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Handbook of pattern recognition & computer vision
Shape from Texture Using Local Spectral Moments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Segmentation of Color Textured Images Using Dual Tree Complex Wavelet Features and Fuzzy Clustering
ICCIMA '05 Proceedings of the Sixth International Conference on Computational Intelligence and Multimedia Applications
Automatic Ultrasound Image Segmentation by Active Contour Model Based on Texture
ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 2
A filter bank for the directional decomposition of images: theoryand design
IEEE Transactions on Signal Processing
Texture image retrieval using new rotated complex wavelet filters
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Texture classification using rotated wavelet filters
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Steerable wedge filters for local orientation analysis
IEEE Transactions on Image Processing
Texture synthesis-by-analysis with hard-limited Gaussian processes
IEEE Transactions on Image Processing
Texture anisotropy in 3-D images
IEEE Transactions on Image Processing
Multidimensional Directional Filter Banks and Surfacelets
IEEE Transactions on Image Processing
Texture analysis and classification with tree-structured wavelet transform
IEEE Transactions on Image Processing
Texture classification and segmentation using wavelet frames
IEEE Transactions on Image Processing
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In this study, four different 2D dual-tree complex wavelet (DT-CWT) based texture feature extraction methods are developed and their applications are demonstrated in segmenting and classifying tissues. Two of the methods use rotation variant texture features and the other two use rotation invariant features. This paper also proposes a novel approach to estimate 3D orientations of tissues based on rotation variant DT-CWT features. The method updates the strongest structural anisotropy direction with an iterative approach and converges to a volume orientation in few steps. Although classification and segmentation results show that there is no significant difference in the performance between rotation variant and invariant features; the latter are more robust to changes in texture rotation, which is essential for classification and segmentation of objects from 3D datasets such as medical tomography images.