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Mean texture depth (MTD) is pivotal in assessing the skid resistance of asphalt pavements and ensuring road safety. This study focuses on developing an automated system for extracting texture features and evaluating MTD based on pavement…

计算机视觉与模式识别 · 计算机科学 2025-01-07 Bingjie Lu , Han-Cheng Dan , Yichen Zhang , Zhetao Huang

High-dimensional limit theorems have been shown useful to derive tuning rules for finding the optimal scaling in random-walk Metropolis algorithms. The assumptions under which weak convergence results are proved are however restrictive: the…

统计方法学 · 统计学 2022-02-16 Sebastian M Schmon , Philippe Gagnon

This paper investigates a novel task of generating texture images from perceptual descriptions. Previous work on texture generation focused on either synthesis from examples or generation from procedural models. Generating textures from…

计算机视觉与模式识别 · 计算机科学 2017-03-30 Yanhai Gan , Huifang Chi , Ying Gao , Jun Liu , Guoqiang Zhong , Junyu Dong

This study addresses the challenge of self-supervised learning for 3D mesh analysis. It presents an new approach that uses random walks as a form of data augmentation to generate diverse representations of mesh surfaces. Furthermore, it…

图形学 · 计算机科学 2025-03-04 Gal Yefet , Ayellet Tal

Texture-based classification solutions have proven their significance in many domains, from industrial inspections to health-related applications. New methods have been developed based on texture feature learning and CNN-based architectures…

计算机视觉与模式识别 · 计算机科学 2022-10-21 Vijay Pandey , Trapti Kalra , Mayank Gubba , Mohammed Faisal

The analysis of the spatial arrangement of colors and roughness/smoothness of figures is relevant due to its wide range of applications. This paper proposes a texture classification method that extracts data from images using the Hilbert…

计算机视觉与模式识别 · 计算机科学 2024-09-25 Aurelio F. Bariviera , Roberta Hansen , Verónica E. Pastor

This work presents a novel descriptor for texture images based on fractal geometry and its application to image analysis. The descriptors are provided by estimating the triangular prism fractal dimension under different scales with a weight…

计算机视觉与模式识别 · 计算机科学 2016-12-21 João B. Florindo , Odemir M. Bruno

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 human viewpoint of…

计算机视觉与模式识别 · 计算机科学 2018-08-03 Swalpa Kumar Roy , Nilavra Bhattacharya , Bhabatosh Chanda , Bidyut B. Chaudhuri , Dipak Kumar Ghosh

Texture recognition is one of the most important tasks in computer vision and, despite the recent success of learning-based approaches, there is still need for model-based solutions. This is especially the case when the amount of data…

计算机视觉与模式识别 · 计算机科学 2020-07-16 Joao Florindo , Konradin Metze

We present a new method for few-shot human motion transfer that achieves realistic human image generation with only a small number of appearance inputs. Despite recent advances in single person motion transfer, prior methods often require a…

计算机视觉与模式识别 · 计算机科学 2021-03-29 Zhichao Huang , Xintong Han , Jia Xu , Tong Zhang

Texture characterization is a central element in many image processing applications. Multifractal analysis is a useful signal and image processing tool, yet, the accurate estimation of multifractal parameters for image texture remains a…

数据分析、统计与概率 · 物理学 2015-05-27 Sébastien Combrexelle , Herwig Wendt , Nicolas Dobigeon , Jean-Yves Tourneret , Steve McLaughlin , Patrice Abry

Texture is a visual attribute largely used in many problems of image analysis. Currently, many methods that use learning techniques have been proposed for texture discrimination, achieving improved performance over previous handcrafted…

计算机视觉与模式识别 · 计算机科学 2020-08-19 Lucas C. Ribas , Leonardo F. S. Scabini , Jarbas Joaci de Mesquita Sá Junior , Odemir M. Bruno

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 many approaches…

计算机视觉与模式识别 · 计算机科学 2018-04-03 Shervan Fekri-Ershad

We present an analytical approach to study simple symmetric random walks (RWs) on a crossing geometry consisting of a plane square lattice crossed by $n_l$ number of lines that all meet each other at a single point (the origin) on the…

统计力学 · 物理学 2019-09-02 Reza Sepehrinia , Abbas Ali Saberi , Hor Dashti-Naserabadi

This note describes a method for detecting dense random texture using fully connected points sampled on image edges. An edge image is randomly sampled with points, the standard L2 distance is calculated between all connected points in a…

计算机视觉与模式识别 · 计算机科学 2023-10-09 Soeren Molander

We propose an unsupervised image segmentation method using features from pre-trained text-to-image diffusion models. Inspired by classic spectral clustering approaches, we construct adjacency matrices from self-attention layers between…

计算机视觉与模式识别 · 计算机科学 2025-11-27 Daniela Ivanova , Marco Aversa , Paul Henderson , John Williamson

In a landscape composed of N randomly distributed sites in Euclidean space, a walker (``tourist'') goes to the nearest one that has not been visited in the last \tau steps. This procedure leads to trajectories composed of a transient part…

无序系统与神经网络 · 物理学 2010-06-10 O. Kinouchi , A. S. Martinez , G. F. Lima , G. M. Lourenco , S. Risau-Gusman

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 patterns (ELBP) with…

图像与视频处理 · 电气工程与系统科学 2018-12-12 Yuting Hu , Zhiling Long , Ghassan AlRegib

Colour and coarseness of skin are visually different. When image processing is involved in the skin analysis, it is important to quantitatively evaluate such differences using texture features. In this paper, we discuss a texture analysis…

计算机视觉与模式识别 · 计算机科学 2010-05-11 A. Sparavigna , R. Marazzato

Graph clustering is an important technique to understand the relationships between the vertices in a big graph. In this paper, we propose a novel random-walk-based graph clustering method. The proposed method restricts the reach of the…

社会与信息网络 · 计算机科学 2016-06-22 Honglei Zhang , Jenni Raitoharju , Serkan Kiranyaz , Moncef Gabbouj