The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Surface shape and curvature scales
Image and Vision Computing
Direct computation of shape cues using scale-adapted spatial derivative operators
International Journal of Computer Vision - Special issue: machine vision research at the Royal Institute of Technology
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons
International Journal of Computer Vision
Texture Classification by Wavelet Packet Signatures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-view Matching for Unordered Image Sets, or "How Do I Organize My Holiday Snaps?"
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Classifying Images of Materials: Achieving Viewpoint and Illumination Independence
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Log-Polar Wavelet Energy Signatures for Rotation and Scale Invariant Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Integrated Edge and Junction Detection with the Boundary Tensor
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
On the Choice of Band-Pass Quadrature Filters
Journal of Mathematical Imaging and Vision
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part II: Bioinspired Applications in Artificial and Natural Computation
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Shape-based Invariant Texture Indexing
International Journal of Computer Vision
IEEE Transactions on Neural Networks
Texture classification by modeling joint distributions of local patterns with Gaussian mixtures
IEEE Transactions on Image Processing
Compressed sensing for robust texture classification
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Sorted random projections for robust rotation-invariant texture classification
Pattern Recognition
On the Use of Low-Pass Filters for Image Processing with Inverse Laplacian Models
Journal of Mathematical Imaging and Vision
Local phase quantization for blur-insensitive image analysis
Image and Vision Computing
Ellipse Invariant Algorithm for Texture Classification
Fundamenta Informaticae
Continuous rotation invariant local descriptors for texton dictionary-based texture classification
Computer Vision and Image Understanding
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Textures within real images vary in brightness, contrast, scale and skew as imaging conditions change. To enable recognition of textures in real images, it is necessary to employ a similarity measure which is invariant to these properties. Furthermore, since textures often appear on undulating surfaces, such invariances must necessarily be local rather than global. Despite these requirements, it is only relatively recently that texture recognition algorithms with local scale and affine invariance properties have begun to be reported. Typically, they comprise detecting feature points followed by geometric normalization prior to description. We describe a method based on invariant combinations of linear filters. Unlike previous methods, we introduce a novel family of filters, which provide scale invariance, resulting in a texture description invariant to local changes in orientation, contrast and scale and robust to local skew. Significantly, the family of filters enable local scale invariants to be defined without using a scale selection principle or a large number of filters. A texture discrimination method based on the 脗2 similarity measure applied to histograms derived from our filter responses outperforms existing methods for retrieval and classification results for both the Brodatz textures and the UIUC database, which has been designed to require local invariance.