Use of gray value distribution of run lengths for texture analysis
Pattern Recognition Letters
Multidimensional Orientation Estimation with Applications to Texture Analysis and Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised feature reduction in image segmentation by local transforms
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Segmentation Using Fractal Dimension
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning Texture Discrimination Masks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Classification Using Windowed Fourier Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Set-Oriented Mining for Association Rules in Relational Databases
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Sampling Large Databases for Association Rules
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Clustering web images using association rules, interestingness measures, and hypergraph partitions
ICWE '06 Proceedings of the 6th international conference on Web engineering
Dare to share: Protecting sensitive knowledge with data sanitization
Decision Support Systems
Data Mining and Its Use in Texture Analysis
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P 2003)
Local relational string and mutual matching for image retrieval
Information Processing and Management: an International Journal
Multiresolution image parametrization for improving texture classification
EURASIP Journal on Advances in Signal Processing
Multi-resolution Image Parametrization in Stepwise Diagnostics of Coronary Artery Disease
AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Towards symbolic mining of images with association rules: Preliminary results on textures
Intelligent Data Analysis - Analysis of Symbolic and Spatial Data
ADaM: a data mining toolkit for scientists and engineers
Computers & Geosciences
Mining spatial gene expression data for association rules
BIRD'07 Proceedings of the 1st international conference on Bioinformatics research and development
Mining frequent itemsets from uncertain data
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Wavelet domain association rules for efficient texture classification
Applied Soft Computing
Data Mining and Its Use in Texture Analysis
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P 2003)
Median binary pattern for textures classification
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
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A new type of texture feature based on association rules is proposed in this paper. Association rules have been used in applications such as market basket analysis to capture relationships present among items in large data sets. It is shown that association rules can be adapted to capture frequently occurring local structures in images. Association rules capture both structural and statistical information, and automatically identifies the structures that occur most frequently and relationships that have significant discriminative power. Methods for classification and segmentation of textured images using association rules as texture features are described. Simulation results using images consisting of man made and natural textures show that association rule features perform well compared to other widely used texture features. It is shown that association rule features can distinguish texture pairs with identical first, second, and third order statistics, and texture pairs that are not easily discriminable visually.