Journal ArticleDOI
Texture analysis using gray level run lengths
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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Proceedings ArticleDOI
Combined Feature Extraction and Selection in Texture Analysis
Zhigang Shang,Mengmeng Li +1 more
TL;DR: A texture feature selection method based on grouped sorting and efficient less ones are selected by the proposed method to be used in the classification of texture features.
Patent
Systems and methods for detecting retinal abnormalities
TL;DR: In this article, the authors proposed methods and systems for detecting retinal abnormalities in fundus images by interdependently smoothing and segmenting the image, identifying retinal features in the smoothed and segmented image and analyzing the identified retinal feature in the image to identify a retinal abnormality.
Proceedings ArticleDOI
Texture analysis using 2D wavelet transform: theory and applications
TL;DR: A survey of recently proposed methods for the analysis of textured images based on multiresolution properties of the two-dimensional wavelet transform, which is used to extract the features needed to discriminate textures.
Journal ArticleDOI
Multi-resolution wavelet-transformed image analysis of histological sections of breast carcinomas.
TL;DR: It is concluded that the best classifier of carcinomas in histological sections of breast tissue are the texture features from the second-level Haar transform wavelet images used in a discriminant function.
Book ChapterDOI
Authentication and Copyright Protection of Videos Under Transmitting Specifications
TL;DR: Invariance to global Rotation, Scaling, Translation (RST) attacks is provided by feature-based approach, and the novelty is in that it does not embed watermark in these stable regions, but coordinates of descriptors as they were in the host frame.
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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