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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Journal ArticleDOI
Carotid artery ultrasound texture, cardiovascular risk factors, and subclinical arterial disease: the Multi-Ethnic Study of Atherosclerosis (MESA)
Carol Mitchell,Claudia E. Korcarz,Matthew C. Tattersall,Adam D. Gepner,Rebekah Young,Wendy S. Post,Joel D. Kaufman,Robyn L. McClelland,James H. Stein +8 more
TL;DR: Findings support the potential use of the ultrasound texture contrast for evaluating arterial injury and CVD risk and describe how the greyscale texture feature "contrast" is related to CVDrisk factors.
Book ChapterDOI
Content-Based Medical Image Retrieval
Henning Müller,Thomas M. Deserno +1 more
TL;DR: This chapter details the necessity for alternative access concepts to the currently mainly text-based methods in medical information retrieval, and discusses evaluation of medical content-based image retrieval (CBIR) systems.
Proceedings ArticleDOI
Identification of stochastic textures with multiresolution features and self-organizing maps
TL;DR: An automatic method of clustering and identifying stochastic textures by means of self-organizing maps is presented to utilize co-occurrence matrices at different resolution levels and to let the self- Organizing process take care of the clustering problem.
Journal ArticleDOI
Textural Defect Segmentation Using a Fourier-Domain Maximum Likelihood Estimation Method
TL;DR: In this paper, a Fourier-domain maximum likelihood estimator (FDMLE) based on the fractional Brownian motion (FBM) model was used to inspect surface defects of textile fabrics.
Journal ArticleDOI
Adaptive classification of textured images using linear prediction and neural networks
TL;DR: This technique uses a fast multichannel algorithm for recursive estimation of autoregressive (AR) texture model parameters, along with a powerful statistical distance measure for adaptive selection of a small representative set of AR texture models.
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.