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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Proceedings ArticleDOI
Blur identification in image processing
J. Da Rugna,Hubert Konik +1 more
TL;DR: The aim of this study is to achieve a blur identification task in still images by discussing here precisely the overall process, from the objective choice of the segmentation algorithm to the presentation of the different introduced descriptors.
Journal ArticleDOI
Data mining on partial discharge signals of power transformer's defect models
TL;DR: In this paper, two classification algorithms are used for the separation of PD sources, decision tree and k-nearest neighbors algorithm, which can help us to identify the type of PD fault in a transformer when the required PD measured data are available.
Proceedings ArticleDOI
Distinction of winter road surface conditions using road surveillance camera
TL;DR: This paper presents a distinction method of road surface conditions of wet or snow by using only visible road surveillance camera at daytime and night-time, which is able to distinguish road surface condition with high accuracy at both daytime and day-time such as wet orSnow.
Book ChapterDOI
Color Image Segmentation
TL;DR: This work developed different segmentation approaches, sweeping from classical color texture to recent color fractal features, in order to express this visual complexity and show how it can be used to express homogeneity, distances, and similarity measures.
Journal ArticleDOI
Differentiation of Intracardiac Tumors and Thrombi by Echocardiography Tissue Characterization: Comparison of an Artificial Neural Network and Human Observers
TL;DR: The feasibility of classifying ultrasound images of intracardiac tumors and thrombi with a neural network‐based algorithm was compared with the performance of experienced echocardiographers, and the network and echOCardiographers agreed in 88% of the images.
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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