Local linear transforms for texture measurements
Signal Processing
Sum and Difference Histograms for Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Decision estimation and classification: an introduction to pattern recognition and related topics
Decision estimation and classification: an introduction to pattern recognition and related topics
Multichannel Texture Analysis Using Localized Spatial Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised texture segmentation using Gabor filters
Pattern Recognition
On texture analysis: local energy transforms versus quadrature filters
Signal Processing
Reduced Multidimensional Co-Occurrence Histograms in Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
A view of the EM algorithm that justifies incremental, sparse, and other variants
Proceedings of the NATO Advanced Study Institute on Learning in graphical models
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons
International Journal of Computer Vision
Signal Processing for Computer Vision
Signal Processing for Computer Vision
Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets
Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computational Statistics & Data Analysis
A Two-Stage-Classifier for Defect Classification in Optical Media Inspection
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Empirical Evaluation of Dissimilarity Measures for Color and Texture
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A Cluster-Based Statistical Model for Object Detection
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
A Statistical Approach to Texture Classification from Single Images
International Journal of Computer Vision - Special Issue on Texture Analysis and Synthesis
A Sparse Texture Representation Using Local Affine Regions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Texture-Based Method for Modeling the Background and Detecting Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image classification using cluster cooccurrence matrices of local relational features
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Signatures versus histograms: Definitions, distances and algorithms
Pattern Recognition
TEXEMS: Texture Exemplars for Defect Detection on Random Textured Surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Locally Rotation, Contrast, and Scale Invariant Descriptors for Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simplifying Mixture Models Using the Unscented Transform
IEEE Transactions on Pattern Analysis and Machine Intelligence
Description of interest regions with local binary patterns
Pattern Recognition
Kernel Codebooks for Scene Categorization
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Image description using joint distribution of filter bank responses
Pattern Recognition Letters
Dominant local binary patterns for texture classification
IEEE Transactions on Image Processing
On bounds of shift variance in two-channel multirate filter banks
IEEE Transactions on Signal Processing
Gaussian Mixture Modeling by Exploiting the Mahalanobis Distance
IEEE Transactions on Signal Processing - Part I
Texture segmentation using filters with optimized energy separation
IEEE Transactions on Image Processing
Comparison of texture features based on Gabor filters
IEEE Transactions on Image Processing
Texture classification using spectral histograms
IEEE Transactions on Image Processing
Design-based texture feature fusion using Gabor filters and co-occurrence probabilities
IEEE Transactions on Image Processing
Successive elimination algorithm for motion estimation
IEEE Transactions on Image Processing
Texture classification and segmentation using wavelet frames
IEEE Transactions on Image Processing
Support vector machines for histogram-based image classification
IEEE Transactions on Neural Networks
Contourlet-based texture classification with product bernoulli distributions
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
Texture classification based on contourlet subband clustering
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
Statistical contourlet subband characterization for texture image retrieval
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
Texture Description Through Histograms of Equivalent Patterns
Journal of Mathematical Imaging and Vision
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Texture classification generally requires the analysis of patterns in local pixel neighborhoods. Statistically, the underlying processes are comprehensively described by their joint probability density functions (jPDFs). Even for small neighborhoods, however, stable estimation of jPDFs by joint histograms (jHSTs) is often infeasible, since the number of entries in the jHST exceeds by far the number of pixels in a typical texture region. Moreover, evaluation of distance functions between jHSTs is often computationally prohibitive. Practically, the number of entries in a jHST is therefore reduced by considering only two-pixel patterns, leading to 2D-jHSTs known as cooccurrence matrices, or by quantization of the gray levels in local patterns to only two gray levels, yielding local binary patterns (LBPs). Both approaches result in a loss of information. We introduce here a framework for supervised texture classification which reduces or avoids this information loss. Local texture neighborhoods are first filtered by a filter bank. Without further quantization, the jPDF of the filter responses is then described parametrically by Gaussian mixture models (GMMs). We show that the parameters of the GMMs can be reliably estimated from small image regions. Moreover, distances between the thus modelled jPDFs of different texture patterns can be computed efficiently in closed form from their model parameters.We furthermore extend this texture descriptor to achieve full invariance to rotation. We evaluate the framework for different filter banks on the Brodatz texture set. We first show that combining the LBP difference filters with the GMM-based density estimator outperforms the classical LBP approach and its codebook extensions. When replacing these--rather elementary-- difference filters by the wavelet frame transform (WFT), the performance of the framework on all 111 Brodatz textures exceeds the one obtained more recently by spin image and RIFT descriptors by Lazebnik et al.