Papers Texture Classification
“Texture Classification” 태그가 달린 논문 206편 · 필터 해제
Characterization of migrated seismic volumes using texture attributes: a comparative study
In this paper, we examine several typical texture attributes developed in the image processing community in recent years with respect to their capability of characterizing a migrated seismic volume. These attributes are …
Image RetrievalRetrievalSeismic InterpretationTexture ClassificationSoil Texture Classification with 1D Convolutional Neural Networks based on Hyperspectral Data
Soil texture is important for many environmental processes. In this paper, we study the classification of soil texture based on hyperspectral data. We develop and implement three 1-dimensional (1D) convolutional neural n…
General ClassificationTexture ClassificationScale Selective Extended Local Binary Pattern for Texture Classification
In this paper, we propose a new texture descriptor, scale selective extended local binary pattern (SSELBP), to characterize texture images with scale variations. We first utilize multi-scale extended local binary pattern…
ClassificationTexture ClassificationCompleted Local Derivative Pattern for Rotation Invariant Texture Classification
In this paper, we propose a new texture descriptor, completed local derivative pattern (CLDP). In contrast to completed local binary pattern (CLBP), which involves only local differences at each scale, CLDP encodes the d…
ClassificationTexture ClassificationSpatial Logics and Model Checking for Medical Imaging (Extended Version)
Recent research on spatial and spatio-temporal model checking provides novel image analysis methodologies, rooted in logical methods for topological spaces. Medical Imaging (MI) is a field where such methods show potenti…
SegmentationTexture ClassificationAtrial fibrosis quantification based on maximum likelihood estimator of multivariate images
We present a fully-automated segmentation and quantification of the left atrial (LA) fibrosis and scars combining two cardiac MRIs, one is the target late gadolinium-enhanced (LGE) image, and the other is an anatomical M…
SegmentationTexture ClassificationRotational 3D Texture Classification Using Group Equivariant CNNs
Convolutional Neural Networks (CNNs) traditionally encode translation equivariance via the convolution operation. Generalization to other transformations has recently received attraction to encode the knowledge of the da…
ClassificationDiversityGeneral ClassificationTexture Classification+1Porosity Amount Estimation in Stones Based on Combination of One Dimensional Local Binary Patterns and Image Normalization Technique
Since now, many approaches has been proposed for surface defect detection based on image texture analysis techniques. One of the efficient texture analysis operations is local binary patterns which provides good accuracy…
Defect DetectionTexture ClassificationDomain-Specific Human-Inspired Binarized Statistical Image Features for Iris Recognition
Binarized statistical image features (BSIF) have been successfully used for texture analysis in many computer vision tasks, including iris recognition and biometric presentation attack detection. One important point is t…
Domain AdaptationIris RecognitionTexture ClassificationDynamic texture analysis with diffusion in networks
Dynamic texture is a field of research that has gained considerable interest from computer vision community due to the explosive growth of multimedia databases. In addition, dynamic texture is present in a wide range of …
Fire DetectionGeneral ClassificationTexture ClassificationFusion of complex networks and randomized neural networks for texture analysis
This paper presents a high discriminative texture analysis method based on the fusion of complex networks and randomized neural networks. In this approach, the input image is modeled as a complex networks and its topolog…
Texture ClassificationConvex Class Model on Symmetric Positive Definite Manifolds
The effectiveness of Symmetric Positive Definite (SPD) manifold features has been proven in various computer vision tasks. However, due to the non-Euclidean geometry of these features, existing Euclidean machineries cann…
ClassificationGeneral ClassificationmodelObject Recognition+3Fast Rotational Sparse Coding
We propose an algorithm for rotational sparse coding along with an efficient implementation using steerability. Sparse coding (also called dictionary learning) is an important technique in image processing, useful in inv…
Dictionary LearningTexture ClassificationClassification-Driven Dynamic Image Enhancement
Convolutional neural networks rely on image texture and structure to serve as discriminative features to classify the image content. Image enhancement techniques can be used as preprocessing steps to help improve the ov…
ClassificationGeneral Classificationimage-classificationImage Classification+2Wavelet Convolutional Neural Networks
Spatial and spectral approaches are two major approaches for image processing tasks such as image classification and object recognition. Among many such algorithms, convolutional neural networks (CNNs) have recently achi…
General Classificationimage-classificationImage ClassificationObject Recognition+1Robust Adaptive Median Binary Pattern for noisy texture classification and retrieval
Texture is an important cue for different computer vision tasks and applications. Local Binary Pattern (LBP) is considered one of the best yet efficient texture descriptors. However, LBP has some notable limitations, mos…
ClassificationGeneral ClassificationRetrievalTexture ClassificationMultilayer Complex Network Descriptors for Color-Texture Characterization
A new method based on complex networks is proposed for color-texture analysis. The proposal consists on modeling the image as a multilayer complex network where each color channel is a layer, and each pixel (in each colo…
Texture ClassificationQuantification of Lung Abnormalities in Cystic Fibrosis using Deep Networks
Cystic fibrosis is a genetic disease which may appear in early life with structural abnormalities in lung tissues. We propose to detect these abnormalities using a texture classification approach. Our method is a cascade…
Texture ClassificationA Review on Image Texture Analysis Methods
Texture classification is an active topic in image processing which plays an important role in many applications such as image retrieval, inspection systems, face recognition, medical image processing, etc. There are man…
Face RecognitionGeneral ClassificationImage RetrievalRetrieval+2Innovative Texture Database Collecting Approach and Feature Extraction Method based on Combination of Gray Tone Difference Matrixes, Local Binary Patterns,and K-means Clustering
Texture analysis and classification are some of the problems which have been paid much attention by image processing scientists since late 80s. If texture analysis is done accurately, it can be used in many cases such as…
ClassificationClusteringGeneral ClassificationObject Tracking+1