Results 11 to 20 of about 102,250 (219)

Deconvolution-segmentation for textured images [PDF]

open access: yes2017 25th European Signal Processing Conference (EUSIPCO), 2017
Publication in the conference proceedings of EUSIPCO, Kos island, Greece ...
Jean-François Giovannelli   +1 more
openaire   +1 more source

Cartoon+Texture Image Decomposition [PDF]

open access: yesImage Processing On Line, 2011
In this article we give a thorough description of the algorithm proposed in [A. Buades, T. Le, J.M. Morel and L. Vese, Fast cartoon + texture image filters, IEEE Transactions on Image Processing, 2010] for cartoon+texture decomposition using of a nonlinear low pass-high pass filter pair.
Antoni Buades   +3 more
openaire   +2 more sources

Texture image analysis and texture classification methods - A review

open access: yesCoRR, 2019
Tactile texture refers to the tangible feel of a surface and visual texture refers to see the shape or contents of the image. In the image processing, the texture can be defined as a function of spatial variation of the brightness intensity of the pixels. Texture is the main term used to define objects or concepts of a given image.
Laleh Armi, Shervan Fekri Ershad
openaire   +2 more sources

Unsupervised Segmentation Of Texture Images [PDF]

open access: yesSPIE Proceedings, 1988
Past work on unsupervised segmentation of a texture image has been based on several restrictive assumptions to reduce the difficulty of this challenging segmentation task. Typically, a fixed number of different texture regions is assumed and each region is assumed to be generated by a simple model.
MICHEL X., LEONARDI, Riccardo, GERSHO A.
openaire   +1 more source

On discriminating visual textures and images [PDF]

open access: yesPerception & Psychophysics, 1982
Recent developments in modeling image discrimination by feature analytic and frequency selective methods are discussed. Some issues relating to the design of two-dimensional spatial frequency filters are developed within the context of two experiments on texture discrimination using artificial and naturally occurring textures.
openaire   +2 more sources

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

open access: yesArthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos   +2 more
wiley   +1 more source

Experimental Evaluation of 100Cr6 Steel Microindented Surfaces Under Lubricated Nonconformal Point Contacts

open access: yesAdvanced Engineering Materials, EarlyView.
The tribological behavior of 100Cr6 steel spheres textured via Vickers microindentation is evaluated under lubricated sliding by varying both dimple size and density. Fine and dense textures significantly reduce friction across all lubrication regimes, while large dimples increase it.
Farideh Davoodi   +3 more
wiley   +1 more source

Texture replacement in real images [PDF]

open access: yesProceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2005
Texture replacement in real images has many applications, such as interior design, digital movie making and computer graphics. The goal is to replace some specified texture patterns in an image while preserving lighting effects, shadows and occlusions.
Yanghai Tsin   +2 more
openaire   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

open access: yesAdvanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice   +2 more
wiley   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

open access: yesAdvanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky   +5 more
wiley   +1 more source

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