Papers Texture Classification
“Texture Classification” 태그가 달린 논문 206편 · 필터 해제
Using Filter Banks in Convolutional Neural Networks for Texture Classification
Deep learning has established many new state of the art solutions in the last decade in areas such as object, scene and speech recognition. In particular Convolutional Neural Network (CNN) is a category of deep learning …
ClassificationGeneral ClassificationObjectobject-detection+4Combined statistical and model based texture features for improved image classification
This paper aims to improve the accuracy of texture classification based on extracting texture features using five different texture methods and classifying the patterns using a naive Bayesian classifier. Three statistica…
General Classificationimage-classificationImage ClassificationTexture ClassificationGraph entropies in texture segmentation of images
We study the applicability of a set of texture descriptors introduced in recent work by the author to texture-based segmentation of images. The texture descriptors under investigation result from applying graph indices f…
Image SegmentationSegmentationSemantic SegmentationTexture ClassificationAssessment of texture measures susceptibility to noise in conventional and contrast enhanced computed tomography lung tumour images
Noise is one of the major problems that hinder an effective texture analysis of disease in medical images, which may cause variability in the reported diagnosis. In this paper seven texture measurement methods (two wavel…
Computed Tomography (CT)Texture Classificationface anti-spoofing based on color texture analysis
Research on face spoofing detection has mainly been focused on analyzing the luminance of the face images, hence discarding the chrominance information which can be useful for discriminating fake faces from genuine ones.…
Face Anti-SpoofingTexture ClassificationVisualizing and Understanding Deep Texture Representations
A number of recent approaches have used deep convolutional neural networks (CNNs) to build texture representations. Nevertheless, it is still unclear how these models represent texture and invariances to categorical vari…
AttributeImage ManipulationScene RecognitionTexture ClassificationBeyond Gauss: Image-Set Matching on the Riemannian Manifold of PDFs
State-of-the-art image-set matching techniques typically implicitly model each image-set with a Gaussian distribution. Here, we propose to go beyond these representations and model image-sets as probability distribution …
Dimensionality ReductionFace RecognitionGeneral Classificationset matching+3BoWFire: Detection of Fire in Still Images by Integrating Pixel Color and Texture Analysis
Emergency events involving fire are potentially harmful, demanding a fast and precise decision making. The use of crowdsourcing image and videos on crisis management systems can aid in these situations by providing more …
Decision MakingFire DetectionGeneral ClassificationManagement+1Fusing Subcategory Probabilities for Texture Classification
Texture, as a fundamental characteristic of objects, has attracted much attention in computer vision research. Performance of texture classification is however still lacking for some challenging cases, largely due to the…
ClassificationClusteringGeneral ClassificationTexture ClassificationA PCA-Based Convolutional Network
In this paper, we propose a novel unsupervised deep learning model, called PCA-based Convolutional Network (PCN). The architecture of PCN is composed of several feature extraction stages and a nonlinear output stage. Par…
Deep LearningFace RecognitionTexture ClassificationSparse Radial Sampling LBP for Writer Identification
In this paper we present the use of Sparse Radial Sampling Local Binary Patterns, a variant of Local Binary Patterns (LBP) for text-as-texture classification. By adapting and extending the standard LBP operator to the pa…
BinarizationGeneral ClassificationTexture ClassificationLOAD: Local Orientation Adaptive Descriptor for Texture and Material Classification
In this paper, we propose a novel local feature, called Local Orientation Adaptive Descriptor (LOAD), to capture regional texture in an image. In LOAD, we proposed to define point description on an Adaptive Coordinate Sy…
General ClassificationMaterial ClassificationMaterial RecognitionTexture ClassificationTexture Retrieval via the Scattering Transform
This work studies the problem of content-based image retrieval, specifically, texture retrieval. It focuses on feature extraction and similarity measure for texture images. Our approach employs a recently developed metho…
Content-Based Image RetrievalImage RetrievalRetrievalTexture ClassificationTexture analysis by multi-resolution fractal descriptors
This work proposes a texture descriptor based on fractal theory. The method is based on the Bouligand-Minkowski descriptors. We decompose the original image recursively into 4 equal parts. In each recursion step, we esti…
General ClassificationTexture ClassificationImproved texture image classification through the use of a corrosion-inspired cellular automaton
In this paper, the problem of classifying synthetic and natural texture images is addressed. To tackle this problem, an innovative method is proposed that combines concepts from corrosion modeling and cellular automata t…
General Classificationimage-classificationImage ClassificationTexture ClassificationGabor wavelets combined with volumetric fractal dimension applied to texture analysis
Texture analysis and classification remain as one of the biggest challenges for the field of computer vision and pattern recognition. On this matter, Gabor wavelets has proven to be a useful technique to characterize dis…
General ClassificationTexture ClassificationFractal descriptors based on the probability dimension: a texture analysis and classification approach
In this work, we propose a novel technique for obtaining descriptors of gray-level texture images. The descriptors are provided by applying a multiscale transform to the fractal dimension of the image estimated through t…
General ClassificationTexture ClassificationTexture analysis using volume-radius fractal dimension
Texture plays an important role in computer vision. It is one of the most important visual attributes used in image analysis, once it provides information about pixel organization at different regions of the image. This …
Texture ClassificationKernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices
Symmetric Positive Definite (SPD) matrices have become popular to encode image information. Accounting for the geometry of the Riemannian manifold of SPD matrices has proven key to the success of many algorithms. However…
Motion SegmentationPedestrian DetectionSegmentationTexture ClassificationAmoeba Techniques for Shape and Texture Analysis
Morphological amoebas are image-adaptive structuring elements for morphological and other local image filters introduced by Lerallut et al. Their construction is based on combining spatial distance with contrast informat…
Texture Classification