Journal ArticleDOI
Texture analysis using gray level run lengths
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TLDR
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.About:
This article is published in Computer Graphics and Image Processing.The article was published on 1975-06-01. It has received 1848 citations till now. The article focuses on the topics: Image texture & Texture (geology).read more
Citations
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Journal ArticleDOI
Making Tactile Textures with Predefined Affective Properties
TL;DR: The principal contribution of the work is the demonstration of a process, using machine vision methods and rapid prototyping, which can be used to make new tactile textures with predefined affective properties.
Journal ArticleDOI
A robust texture feature extraction using the localized angular phase
TL;DR: The experimental results show that the classification performance of LAP in terms of the latter application examples are better than those of local phase quantization (LPQ), local binary patterns (LBP), and local Fourier histogram (LFH).
Journal ArticleDOI
An efficient classification approach for detection of Alzheimer’s disease from biomedical imaging modalities
TL;DR: An automated reliable system for the detection of AD affected patients accurately from the brain images of sMRI and a novel classification technique is proposed by combining the Kernel fuzzy c-means clustering and Back-propagation artificial neural network to categorize NC, MCI and AD from the brains of s MRI.
Proceedings ArticleDOI
Texture based image recognition in microscopy images of diffuse gliomas with multi-class gentle boosting mechanism
TL;DR: An automatic method for identifying critical diagnostic regions within whole-slide microscopy images of gliomas by frame the problem of critical region identification as a texture-based content retrieval task in the sense that each image is represented by a set of texture features.
Journal ArticleDOI
MRI radiomics for the prediction of recurrence in patients with clinically non-functioning pituitary macroadenomas.
Leonardo F. Machado,Paula Conde Lamparelli Elias,Ayrton Custódio Moreira,Antonio Carlos dos Santos,Luiz Otavio Murta Junior +4 more
TL;DR: Three-dimensional Radiomics have superior discrimination power to predict NFPA recurrence than two-dimensional radiomic features, and the combination of Radiomic with machine-learning algorithms can offer computational models capable of non-invasive, unbiased, and quick assessment that might improve the prediction of NFPARecurrence.
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
Gray-Level Manipulation Experiments for Texture Analysis
TL;DR: Some gray-level manipulation techniques are described, the first of which involves changing thegray-level distribution within the picture, and a method for extracting relatively noise-free objects from a noisy background is described.
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