Sum and Difference Histograms for Texture Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture Segmentation Using Voronoi Polygons
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture classification using texture spectrum
Pattern Recognition
Handbook of pattern recognition & computer vision
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Computer Analysis of Visual Textures
Computer Analysis of Visual Textures
One-class texture classifier in the CCR feature space
Pattern Recognition Letters
Comparative experiment with colour texture classifiers using the CCR feature space
Pattern Recognition Letters
Rotation-invariant colour texture classification through multilayer CCR
Pattern Recognition Letters
Texture classification through combination of sequential colour texture classifiers
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Texture Description Through Histograms of Equivalent Patterns
Journal of Mathematical Imaging and Vision
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A statistical approach based on the coordinated clusters representation of images is used for classification and recognition of textured images. The ability of the descriptor to capture spatial statistical features of an image is exploited. A binarization needed for image preprocessing is done using, but not restricted to, a fuzzy clustering algorithm. A normalized spectrum histogram of the coordinated cluster representation is used as a unique feature vector, and a simple minimum distance classifier is used for classification purposes. Using the size and the number of subimages for prototype generation and the size of the test images as the parameters in the learning and recognition phases, we establish the regions of reliable classification in the space of subimage parameters. The results of classification tests show the high performance of the proposed method that may have industrial application for texture classification.