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Journal ArticleDOI

A Comparative Study of Texture Measures for Terrain Classification

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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.

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Citations
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Journal ArticleDOI

Noisy fingerprint classification using multilayer perceptron with fuzzy geometrical and textural features

TL;DR: A multilayer perceptron is used for the classification of noisy fingerprint patterns and the generalization ability of the model in handling distorted fingerprint images is demonstrated.
Journal ArticleDOI

Assistive system based on nerve detection and needle navigation in ultrasound images for regional anesthesia

TL;DR: This work presents the first fully automatic system for the detection of regions of interest and generation of the needle trajectory in ultrasound images for UGRA, and demonstrates the robustness of the proposed scheme and the feasibility of such an assistive system.
Journal ArticleDOI

Machine learning based liver disease diagnosis: A systematic review

- 01 Jan 2022 - 
TL;DR: In this article , a detailed analysis of computer-aided diagnosis of hepatic lesions in view of diffuse-and focal liver disorders is presented, with pros and cons for each preliminary step, particularly preprocessing, attribute analysis, and classification techniques to accomplish clinical diagnostic tasks.
Journal ArticleDOI

Noninvasive diagnosis of cardiac rejection through echocardiographic tissue characterization

TL;DR: It is concluded that cardiac rejection is associated with echocardiographic texture alterations and that serial echocentreographic texture analysis can reliably identify rejection.
Journal ArticleDOI

Texture classification of machined surfaces using image processing and machine learning techniques

TL;DR: The efficiency of proposed methodology, which is useful for identifying texture images, is demonstrated, is found that Artificial Neural Network and Random forest give100 % training accuracy and 99% cross validation accuracy.
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

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.