Local linear transforms for texture measurements
Signal Processing
Recursive Regularization Filters: Design, Properties, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multidimensional Orientation Estimation with Applications to Texture Analysis and Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
A simplified approach to the HMM based texture analysis and its application to document segmentation
Pattern Recognition Letters
Segmentation of Color Textures
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Visualization and Computer Graphics
The L/sub 2/-Polynomial Spline Pyramid
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Classification by Wavelet Packet Signatures
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture classification using wavelet transform
Pattern Recognition Letters
Texture segmentation using wavelet transform
Pattern Recognition Letters
Classification of honeybee pollen using a multiscale texture filtering scheme
Machine Vision and Applications
Reduced Complexity Rotation Invariant Texture Classification Using a Blind Deconvolution Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-scale morphological modeling of a class of structural texture
Machine Graphics & Vision International Journal
Texture classification using ridgelet transform
Pattern Recognition Letters
Expert Systems with Applications: An International Journal
Texture classification using ridgelet transform
Pattern Recognition Letters
Automated barcode recognition for smart identification and inspection automation
Expert Systems with Applications: An International Journal
EURASIP Journal on Applied Signal Processing
Wavelet-based modeling of singular values for image texture classification
Machine Graphics & Vision International Journal
Image texture classification using wavelet packet transform and probabilistic neural network
Intelligent Data Analysis
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Rotation- and scale-invariant texture classification using log-polar and ridgelet transforms
Machine Graphics & Vision International Journal
Texture segmentation using hierarchical wavelet decomposition
Pattern Recognition
Evolving descriptors for texture segmentation
Pattern Recognition
Residues of morphological filtering by reconstruction for texture classification
Pattern Recognition
Texture analysis with a texture matched M-channel wavelet approach
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: image and multidimensional signal processing - Volume V
Application of wavelet transforms and bayes classifier to segmentation of ultrasound images
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part II
Texture fuzzy segmentation using adaptive affinity functions
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Proceedings of the 5th IBM Collaborative Academia Research Exchange Workshop
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An approach is described for unsupervised segmentation of textured images. Local texture properties are extracted using local linear transforms that have been optimized for maximal texture discrimination. Local statistics (texture energy measures) are estimated at the output of an equivalent filter bank by means of a nonlinear transformation (absolute value) followed by an iterative Gaussian smoothing algorithm. This procedure generates a multiresolution sequence of feature planes with a half-octave scale progression. A feature reduction technique is then applied to the data and is determined by simultaneously diagonalizing scatter matrices evaluated at two different spatial resolutions. This approach provides a good approximation of R.A. Fisher's (1950) multiple linear discriminants and has the advantage of requiring no a priori knowledge. This feature reduction methods appears to be an improvement on the commonly used Karhunen-Loeve transform and allows efficient texture segmentation based on simple thresholding.