Papers Texture Classification
“Texture Classification” 태그가 달린 논문 206편 · 필터 해제
Fast and accurate computation of orthogonal moments for texture analysis
In this work we describe a fast and stable algorithm for the computation of the orthogonal moments of an image. Indeed, orthogonal moments are characterized by a high discriminative power, but some of their possible form…
General ClassificationTexture ClassificationTexture Classification in Extreme Scale Variations using GANet
Research in texture recognition often concentrates on recognizing textures with intraclass variations such as illumination, rotation, viewpoint and small scale changes. In contrast, in real-world applications a change in…
ClassificationGeneral ClassificationTexture ClassificationTexture Segmentation Based Video Compression Using Convolutional Neural Networks
There has been a growing interest in using different approaches to improve the coding efficiency of modern video codec in recent years as demand for web-based video consumption increases. In this paper, we propose a mode…
Texture ClassificationVideo CompressionFrom BoW to CNN: Two Decades of Texture Representation for Texture Classification
Texture is a fundamental characteristic of many types of images, and texture representation is one of the essential and challenging problems in computer vision and pattern recognition which has attracted extensive resear…
AttributeGeneral ClassificationSurveyTexture ClassificationFWLBP: A Scale Invariant Descriptor for Texture Classification
In this paper we propose a novel texture descriptor called Fractal Weighted Local Binary Pattern (FWLBP). The fractal dimension (FD) measure is relatively invariant to scale-changes, and presents a good correlation with …
ClassificationGeneral ClassificationTexture ClassificationUV-GAN: Adversarial Facial UV Map Completion for Pose-invariant Face Recognition
Recently proposed robust 3D face alignment methods establish either dense or sparse correspondence between a 3D face model and a 2D facial image. The use of these methods presents new challenges as well as opportunities …
3D Face AlignmentFace AlignmentFace ModelFace Recognition+2Automatic Segmentation and Overall Survival Prediction in Gliomas using Fully Convolutional Neural Network and Texture Analysis
In this paper, we use a fully convolutional neural network (FCNN) for the segmentation of gliomas from Magnetic Resonance Images (MRI). A fully automatic, voxel based classification was achieved by training a 23 layer de…
General ClassificationPredictionSurvival PredictionTexture ClassificationHuman activity recognition from mobile inertial sensors using recurrence plots
Inertial sensors are present in most mobile devices nowadays and such devices are used by people during most of their daily activities. In this paper, we present an approach for human activity recognition based on inerti…
Activity RecognitionGeneral ClassificationHuman Activity RecognitionTexture ClassificationLocal Jet Pattern: A Robust Descriptor for Texture Classification
Methods based on local image features have recently shown promise for texture classification tasks, especially in the presence of large intra-class variation due to illumination, scale, and viewpoint changes. Inspired by…
ClassificationGeneral ClassificationTexture ClassificationDeep Local Binary Patterns
Local Binary Pattern (LBP) is a traditional descriptor for texture analysis that gained attention in the last decade. Being robust to several properties such as invariance to illumination translation and scaling, LBPs ac…
Texture ClassificationTranslationClassification 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 ove…
ClassificationGeneral Classificationimage-classificationImage Classification+2A concatenating framework of shortcut convolutional neural networks
It is well accepted that convolutional neural networks play an important role in learning excellent features for image classification and recognition. However, in tradition they only allow adjacent layers connected, limi…
ClassificationGender ClassificationGeneral Classificationimage-classification+3Locally-Transferred Fisher Vectors for Texture Classification
Texture classification has been extensively studied in computer vision. Recent research shows that the combination of Fisher vector (FV) encoding and convolutional neural network (CNN) provides significant improvement in…
ClassificationGeneral Classificationimage-classificationImage Classification+1Visualizing and Improving Scattering Networks
Scattering Transforms (or ScatterNets) introduced by Mallat are a promising start into creating a well-defined feature extractor to use for pattern recognition and image classification tasks. They are of particular inter…
General Classificationimage-classificationImage ClassificationTexture Classificatione-Counterfeit: a mobile-server platform for document counterfeit detection
This paper presents a novel application to detect counterfeit identity documents forged by a scan-printing operation. Texture analysis approaches are proposed to extract validation features from security background that …
Texture ClassificationWavelet Convolutional Neural Networks for Texture Classification
Texture classification is an important and challenging problem in many image processing applications. While convolutional neural networks (CNNs) achieved significant successes for image classification, texture classifica…
ClassificationGeneral Classificationimage-classificationImage Classification+1Affine-Gradient Based Local Binary Pattern Descriptor for Texture Classiffication
We present a novel Affine-Gradient based Local Binary Pattern (AGLBP) descriptor for texture classification. It is very hard to describe complicated texture using single type information, such as Local Binary Pattern (LB…
feature selectionGeneral ClassificationTexture ClassificationA Gabor Filter Texture Analysis Approach for Histopathological Brain Tumor Subtype Discrimination
Meningioma brain tumour discrimination is challenging as many histological patterns are mixed between the different subtypes. In clinical practice, dominant patterns are investigated for signs of specific meningioma path…
General ClassificationTexture ClassificationA Hybrid Deep Learning Approach for Texture Analysis
Texture classification is a problem that has various applications such as remote sensing and forest species recognition. Solutions tend to be custom fit to the dataset used but fails to generalize. The Convolutional Neur…
ClassificationDeep LearningGeneral ClassificationTexture ClassificationConvolutional Neural Network on Three Orthogonal Planes for Dynamic Texture Classification
Dynamic Textures (DTs) are sequences of images of moving scenes that exhibit certain stationarity properties in time such as smoke, vegetation and fire. The analysis of DT is important for recognition, segmentation, synt…
General ClassificationRetrievalTexture ClassificationVideo Recognition