Journal ArticleDOI
A Comparative Study of Texture Measures for Terrain Classification
Joan S. Weszka,Charles R. Dyer,Azriel Rosenfeld +2 more
- Vol. 6, Iss: 4, pp 269-285
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TLDR
In this paper, three standard approaches to automatic texture classification make use of features based on the Fourier power spectrum, on second-order gray level statistics, and on first-order statistics of gray level differences, respectively.Abstract:
Three standard approaches to automatic texture classification make use of features based on the Fourier power spectrum, on second-order gray level statistics, and on first-order statistics of gray level differences, respectively. Feature sets of these types, all designed analogously, were used to classify two sets of terrain samples. It was found that the Fourier features generally performed more poorly, while the other feature sets all performned comparably.read more
Citations
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Dissertation
Perceptual texture similarity estimation
TL;DR: The results indicate that long-range interactions do provide humans with important cues for the perception of texture similarity, and a new set of contour-based features are developed that can encode such data.
Proceedings ArticleDOI
Textures: an approach for new abstract description language
TL;DR: This work proposes a promising improvement for texture classification and description in the context of natural textures, and establishes a relation between these visual properties used by a human observer, and statistical textural features computed out of the digital image data.
A Multi Agent Approach for Texture Based Classification and Retrieval (MATBCR) using Binary Decision Tree
TL;DR: A simple, novel and yet effective method for classifying and retrieving images based on texture descriptor, the MATBCR model results have been compared with other Texture Based Retrieval System and better prediction accuracy has been observed.
Proceedings ArticleDOI
Evaluation of texture analysis techniques for quantitative characterization of ultrasonic liver images
Sotiris Pavlopoulos,G. Konnis,Efthyvoulos Kyriacou,Dimitris Koutsouris,P. Zoumpoulis,I. Theotokas +5 more
TL;DR: The combination of the two techniques proved to differentiate the three types of ultrasonic liver tissue characterization with an overall accuracy of 81.7%.
Book ChapterDOI
Textile Recognition Using Tchebichef Moments of Co-occurrence Matrices
Marc Cheong,Kar Seng Loke +1 more
TL;DR: The Tchebichef orthogonal polynomial is used as a way to preserve the shape information of co-occurrence matrices generated using the RGB multispectral method; allowing prominent features and shapes of the matrices to be preserved while discarding extraneous information.
References
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Journal ArticleDOI
Textural Features for Image Classification
TL;DR: These results indicate that the easily computable textural features based on gray-tone spatial dependancies probably have a general applicability for a wide variety of image-classification applications.
Journal ArticleDOI
Texture analysis using gray level run lengths
TL;DR: In this paper, a set of texture features based on gray level run lengths is described, and good classification results are obtained with these features on a sets of samples representing nine terrain types.
Proceedings Article
Computer description of textured surfaces
TL;DR: This work deals with computer analysis of textured surfaces with descriptions of textures formalized from natural language descriptions obtained from the directional and non-directional components of the Fourier transform power spectrum.
Spectral and textural processing of ERTS imagery
R. M. Haralick,R. J. Bosley +1 more
TL;DR: In this article, a procedure is developed to simultaneously extract textural features from all bands of ERTS multispectral scanner imagery for automatic analysis, and an ellipsoidally symmetric functional form is assumed for the co-occurrence distribution of multiimage greytone N-tuple differences.