Papers Texture Classification
“Texture Classification” 태그가 달린 논문 206편 · 필터 해제
Texture segmentation with Fully Convolutional Networks
In the last decade, deep learning has contributed to advances in a wide range computer vision tasks including texture analysis. This paper explores a new approach for texture segmentation using deep convolutional neural …
SegmentationTexture ClassificationImproving LBP and its variants using anisotropic diffusion
The main purpose of this paper is to propose a new preprocessing step in order to improve local feature descriptors and texture classification. Preprocessing is implemented by using transformations which help highlight s…
General ClassificationTexture ClassificationTexture Classification of MR Images of the Brain in ALS using CoHOG
Texture analysis is a well-known research topic in computer vision and image processing and has many applications. Gradient-based texture methods have become popular in classification problems. For the first time we exte…
General ClassificationSpecificityTexture ClassificationTexture Characterization by Using Shape Co-occurrence Patterns
Texture characterization is a key problem in image understanding and pattern recognition. In this paper, we present a flexible shape-based texture representation using shape co-occurrence patterns. More precisely, textur…
DescriptiveTexture ClassificationHolistic Interstitial Lung Disease Detection using Deep Convolutional Neural Networks: Multi-label Learning and Unordered Pooling
Accurately predicting and detecting interstitial lung disease (ILD) patterns given any computed tomography (CT) slice without any pre-processing prerequisites, such as manually delineated regions of interest (ROIs), is a…
Computed Tomography (CT)Multi-Label LearningTexture ClassificationSparse-TDA: Sparse Realization of Topological Data Analysis for Multi-Way Classification
Topological data analysis (TDA) has emerged as one of the most promising techniques to reconstruct the unknown shapes of high-dimensional spaces from observed data samples. TDA, thus, yields key shape descriptors in the …
General ClassificationTexture ClassificationTopological Data AnalysisMultivariate mixture model for myocardium segmentation combining multi-source images
This paper proposes a method for simultaneous segmentation of multi-source images, using the multivariate mixture model (MvMM) and maximum of log-likelihood (LL) framework. The segmentation is a procedure of texture clas…
Myocardium SegmentationSegmentationTexture ClassificationThe Mehler-Fock Transform and some Applications in Texture Analysis and Color Processing
Many stochastic processes are defined on special geometrical objects like spheres and cones. We describe how tools from harmonic analysis, i.e. Fourier analysis on groups, can be used to investigate probability density f…
RelationTexture ClassificationMulti-source Transfer Learning with Convolutional Neural Networks for Lung Pattern Analysis
Early diagnosis of interstitial lung diseases is crucial for their treatment, but even experienced physicians find it difficult, as their clinical manifestations are similar. In order to assist with the diagnosis, comput…
Medical Image AnalysisTexture ClassificationTransfer LearningTexture analysis using deterministic partially self-avoiding walk with thresholds
In this paper, we propose a new texture analysis method using the deterministic partially self-avoiding walk performed on maps modified with thresholds. In this method, two pixels of the map are neighbors if the Euclidea…
Texture ClassificationFast deterministic tourist walk for texture analysis
Deterministic tourist walk (DTW) has attracted increasing interest in computer vision. In the last years, different methods for analysis of dynamic and static textures were proposed. So far, all works based on the DTW fo…
General ClassificationTexture ClassificationEvaluating Urbanization from Satellite and Aerial Images by means of a statistical approach to the texture analysis
Statistical methods are usually applied in the processing of digital images for the analysis of the textures displayed by them. Aiming to evaluate the urbanization of a given location from satellite or aerial images, her…
Texture ClassificationDocument Image Coding and Clustering for Script Discrimination
The paper introduces a new method for discrimination of documents given in different scripts. The document is mapped into a uniformly coded text of numerical values. It is derived from the position of the letters in the …
ClusteringTexture ClassificationA probabilistic patch based image representation using Conditional Random Field model for image classification
In this paper we proposed an ordered patch based method using Conditional Random Field (CRF) in order to encode local properties and their spatial relationship in images to address texture classification, face recognitio…
ClassificationFace RecognitionGeneral Classificationimage-classification+3Equiangular Kernel Dictionary Learning With Applications to Dynamic Texture Analysis
Most existing dictionary learning algorithms consider a linear sparse model, which often cannot effectively characterize the nonlinear properties present in many types of visual data, e.g. dynamic texture (DT). Such non…
Computational EfficiencyDictionary LearningTexture ClassificationA Theoretical Analysis of Deep Neural Networks for Texture Classification
We investigate the use of Deep Neural Networks for the classification of image datasets where texture features are important for generating class-conditional discriminative representations. To this end, we first derive t…
ClassificationGeneral ClassificationObject RecognitionTexture ClassificationLearning rotation invariant convolutional filters for texture classification
We present a method for learning discriminative filters using a shallow Convolutional Neural Network (CNN). We encode rotation invariance directly in the model by tying the weights of groups of filters to several rotated…
ClassificationGeneral Classificationimage-classificationImage Classification+1Fractal Dimension Invariant Filtering and Its CNN-based Implementation
Fractal analysis has been widely used in computer vision, especially in texture image processing and texture analysis. The key concept of fractal-based image model is the fractal dimension, which is invariant to bi-Lipsc…
Texture ClassificationA non-extensive entropy feature and its application to texture classification
This paper proposes a new probabilistic non-extensive entropy feature for texture characterization, based on a Gaussian information measure. The highlights of the new entropy are that it is bounded by finite limits and t…
General ClassificationTexture ClassificationQuantification of Ultrasonic Texture heterogeneity via Volumetric Stochastic Modeling for Tissue Characterization
Intensity variations in image texture can provide powerful quantitative information about physical properties of biological tissue. However, tissue patterns can vary according to the utilized imaging system and are intri…
Texture Classification