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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Proceedings ArticleDOI
Picture-graphics color image classification
TL;DR: This paper's image classification algorithm uses three low-level image features: texture, color, and edge characteristics to classify a color image into two classes: business graphics or natural picture.
Journal ArticleDOI
A dynamic classifier selection and combination approach to image region labelling
Sameer Singh,Maneesha Singh +1 more
TL;DR: A new knowledge-based predictive approach based on estimating the Mahalanobis distance between test sample feature values and the corresponding probability distribution function from training data that selectively triggers classifiers is proposed.
Proceedings ArticleDOI
GLDH based analysis of texture anisotropy and symmetry: an experimental study
TL;DR: The author proposes a computationally efficient extension of CPM and GLDH to arbitrary angle and spacing and applies it to the analysis of texture anisotropy and considers the possibility of investigating the symmetry of a texture pattern via the symmetry properties of a polar diagram describing the anisOTropy of the pattern.
Journal ArticleDOI
Nondestructive grading of black tea based on physical parameters by texture analysis
TL;DR: This paper describes a technique to discriminate between four different grades of made black tea using textural features based on grey tone spatial dependencies using the multi-layer perceptron (MLP) technique.
Journal ArticleDOI
Two-Dimensional Fast Fourier Transform and Power Spectrum for Surface Roughness in three Dimensions:
TL;DR: In this article, a detailed procedure to implement the two-dimensional fast Fourier transform and power spectrum for surface roughness in 3D is described, along with theoretical analysis and visual characterization of the presented spectrums.
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.