Pattern Spectrum and Multiscale Shape Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Texture feature performance for image segmentation
Pattern Recognition
Handbook of pattern recognition & computer vision
Texture Classification Using Windowed Fourier Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Off-Line Signature Verification by Local Granulometric Size Distributions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Morphologically Constrained GRFs: Applications to Texture Synthesis and Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Filtering for Texture Classification: A Comparative Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Descriptors of Binary Shapes with Applications
International Journal of Computer Vision
Short communication: The use of Boolean model for texture analysis of grey images
Computer Vision and Image Understanding
SIBGRAPHI '98 Proceedings of the International Symposium on Computer Graphics, Image Processing, and Vision
Texture Analysis Using Morphological Pattern Spectrum and Optimization of Structuring Elements
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Classification of binary textures using the 1-D Boolean model
IEEE Transactions on Image Processing
Extended fractal analysis for texture classification and segmentation
IEEE Transactions on Image Processing
Granulometric analysis of corneal endothelium specular images by using a germ-grain model
Computers in Biology and Medicine
Size-density spectra and their application to image classification
Pattern Recognition
Combining similarity measures in content-based image retrieval
Pattern Recognition Letters
A Comparison of Spatial Pattern Spectra
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
SPPRA '08 Proceedings of the Fifth IASTED International Conference on Signal Processing, Pattern Recognition and Applications
Color text image binarization based on binary texture analysis
Pattern Recognition Letters
Color text image binarization based on binary texture analysis
Pattern Recognition Letters
A new wavelet-based texture descriptor for image retrieval
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Shape-based Invariant Texture Indexing
International Journal of Computer Vision
CLEF'09 Proceedings of the 10th international conference on Cross-language evaluation forum: multimedia experiments
Fast granular analysis based on watershed in microscopic mineral images
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Multimedia retrieval in a medical image collection: results using modality classes
MCBR-CDS'12 Proceedings of the Third MICCAI international conference on Medical Content-Based Retrieval for Clinical Decision Support
An improved distance-based relevance feedback strategy for image retrieval
Image and Vision Computing
Computer Methods and Programs in Biomedicine
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This paper proposes new descriptors for binary and gray-scale images based on newly defined spatial size distributions(SSD). The main idea consists of combining a granulometric analysis of the image with a comparison between the geometric covariograms for binary images or the auto-correlation function for gray-scale images of the original image and its granulometric transformation; the usual granulometric size distribution then arises as a particular case of this formulation. Examples are given to show that in those cases in which a finer description of the image is required, the more complex descriptors generated from the SSD could be advantageously used. It is also shown that the new descriptors are probability distributions so their intuitive interpretation and properties can be appropriately studied from the probabilistic point of view. The usefulness of these descriptors in shape analysis is illustrated by some synthetic examples and their use in texture analysis is studied by doing an experiment of texture classification on a standard texture database. A comparison is perfomed among various cases of the SSD and several former methods for texture classification in terms of percentages of correct classification and the number of features used.