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Artículos de revistas sobre el tema "Images texturées"

Autor: Grafiati

Publicado: 1 de junio de 2024

Última modificación: 19 de julio de 2025

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1

Girod, Luc, and Marc Pierrot-Deseilligny. "L'Égalisation radiométrique de nuages de points 3D issus de corrélation dense." Revue Française de Photogrammétrie et de Télédétection, no. 206 (June 19, 2014): 3–14. http://dx.doi.org/10.52638/rfpt.2014.90.

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Si les problèmes de colorimétrie dans le mosaïquage d'images ont fait l'objet d'études approfondies par le passé et qu'ils sont maintenant globalement résolus, il n'en est pas de même pour l'égalisation des scènes non planaires et des produits photogrammétriques 3D associés. En effet, certains produits photogrammétriques ne sont pas des images mais des produits purement 3D, de type nuage de points ou surfaces texturées, notamment. Cependant, la cohérence colorimétrique reste d'une grande importance dans ces cas pour une visualisation plus fluide des résultats. Cet article explore donc des algo

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2

Boussidi, Brahim, Ronan Fablet, Emmanuelle Autret, and Bertrand Chapron. "Accroissement stochastique de la résolution spatiale des traceurs géophysiques de l'océan: application aux observations satellitaires de la température de surface de l'océan." Revue Française de Photogrammétrie et de Télédétection, no. 202 (April 16, 2014): 66–78. http://dx.doi.org/10.52638/rfpt.2013.52.

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Le développement des capteurs satellitaires d'observation des traceurs géophysiques à la surface de l'océan et les algorithmes de traitement associés ont connu un essor important au cours des vingt dernières années. Les différents capteurs satellitaires disponibles présentent des résolutions spatiales et temporelles différentes ainsi que différents niveaux de sensibilité à la couverture nuageuse. Dans le cas des images de température de surface de la mer, ceci se traduit notamment par de forts taux de données manquantes dans les observations de très haute-résolution (de l'ordre de 1kmx1km) con

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3

Hemalatha, S., and S. Margret Anouncia. "A Computational Model for Texture Analysis in Images with Fractional Differential Filter for Texture Detection." International Journal of Ambient Computing and Intelligence 7, no. 2 (2016): 93–113. http://dx.doi.org/10.4018/ijaci.2016070105.

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This paper is dedicated to the modelling of textured images influenced by fractional derivatives for texture detection. As most of the images contain textures, texture analysis becomes the most important for image understanding and it is a key solution for many computer vision applications. Hence, texture must be suitably detected and represented. Nevertheless, existing texture detection algorithms consider texture as a unique feature from edges. The proposed model explores a novel way of developing texture detection algorithm by mimicking edge detection algorithms. The method assumes that tex

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4

Bhaumik, Shubrajit, Viorel Paleu, Dhrubajyoti Chowdhury, et al. "Tribological Investigation of Textured Surfaces in Starved Lubrication Conditions." Materials 15, no. 23 (2022): 8445. http://dx.doi.org/10.3390/ma15238445.

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The present work investigates the friction reduction capability of two types of micro-textures (grooves and dimples) created on steel surfaces using a vertical milling machine. The wear studies were conducted using a pin-on-disc tribometer, with the results indicating a better friction reduction capacity in the case of the dimple texture as compared to the grooved texture. The microscopic images of the pin surface revealed deep furrows and significant damage on the pin surfaces of the groove-textured disc. An optimization of the textured surfaces was performed using an artificial neural networ

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5

Oliveira, Miguel, Gi-Hyun Lim, Tiago Madeira, Paulo Dias, and Vítor Santos. "Robust Texture Mapping Using RGB-D Cameras." Sensors 21, no. 9 (2021): 3248. http://dx.doi.org/10.3390/s21093248.

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The creation of a textured 3D mesh from a set of RGD-D images often results in textured meshes that yield unappealing visual artifacts. The main cause is the misalignments between the RGB-D images due to inaccurate camera pose estimations. While there are many works that focus on improving those estimates, the fact is that this is a cumbersome problem, in particular due to the accumulation of pose estimation errors. In this work, we conjecture that camera poses estimation methodologies will always display non-neglectable errors. Hence, the need for more robust texture mapping methodologies, ca

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6

Moldir, Yessenova, Abdikerimova Gulzira, Baitemirova Nurgul, et al. "The applicability of informative textural features for the detection of factors negatively influencing the growth of wheat on aerial images." Eastern-European Journal of Enterprise Technologies 4, no. 2 (118) (2022): 51–58. https://doi.org/10.15587/1729-4061.2022.263433.

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Automated processing of aerospace information makes it possible to effectively solve scientific and applied problems in cartography, ecology, oceanology, exploration and development of minerals, agriculture and forestry, and many other areas. At the same time, the main way to extract information is to decipher images, which are the main carrier of information about the area. Aerospace images are a combination of natural texture regions and man-made objects. This article discusses methods for analyzing texture images. The main tasks of the analysis of texture areas include the selection and for

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7

Wen, Mingyun, Jisun Park, and Kyungeun Cho. "Textured Mesh Generation Using Multi-View and Multi-Source Supervision and Generative Adversarial Networks." Remote Sensing 13, no. 21 (2021): 4254. http://dx.doi.org/10.3390/rs13214254.

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This study focuses on reconstructing accurate meshes with high-resolution textures from single images. The reconstruction process involves two networks: a mesh-reconstruction network and a texture-reconstruction network. The mesh-reconstruction network estimates a deformation map, which is used to deform a template mesh to the shape of the target object in the input image, and a low-resolution texture. We propose reconstructing a mesh with a high-resolution texture by enhancing the low-resolution texture through use of the super-resolution method. The architecture of the texture-reconstruction

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8

Kang, Junhua, Fei Deng, Xinwei Li, and Fang Wan. "AUTOMATIC TEXTURE RECONSTRUCTION OF 3D CITY MODEL FROM OBLIQUE IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 341–47. http://dx.doi.org/10.5194/isprsarchives-xli-b1-341-2016.

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In recent years, the photorealistic 3D city models are increasingly important in various geospatial applications related to virtual city tourism, 3D GIS, urban planning, real-estate management. Besides the acquisition of high-precision 3D geometric data, texture reconstruction is also a crucial step for generating high-quality and visually realistic 3D models. However, most of the texture reconstruction approaches are probably leading to texture fragmentation and memory inefficiency. In this paper, we introduce an automatic framework of texture reconstruction to generate textures from oblique

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9

Kang, Junhua, Fei Deng, Xinwei Li, and Fang Wan. "AUTOMATIC TEXTURE RECONSTRUCTION OF 3D CITY MODEL FROM OBLIQUE IMAGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B1 (June 3, 2016): 341–47. http://dx.doi.org/10.5194/isprs-archives-xli-b1-341-2016.

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In recent years, the photorealistic 3D city models are increasingly important in various geospatial applications related to virtual city tourism, 3D GIS, urban planning, real-estate management. Besides the acquisition of high-precision 3D geometric data, texture reconstruction is also a crucial step for generating high-quality and visually realistic 3D models. However, most of the texture reconstruction approaches are probably leading to texture fragmentation and memory inefficiency. In this paper, we introduce an automatic framework of texture reconstruction to generate textures from oblique

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10

Volkova, Natalya P., and Viktor N. Krylov. "VECTOR-DIFFERENCE TEXTURE SEGMENTATION METHOD IN TECHNICAL AND MEDICAL EXPRESS DIAGNOSTIC SYSTEMS." Herald of Advanced Information Technology 3, no. 4 (2020): 226–39. http://dx.doi.org/10.15276/hait.04.2020.2.

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The study shows the need for express systems, in which it is necessary to perform the analysis of texture images in various areas of diagnosis, for example, in medical express diagnostics of dermatologic disorders. Since the reliability of decision-making in such systems depends on the quality of image segmentation, which, as a rule, have the nature of spectral-statistical textures, it is advisable to develop methods for segmentation of such images and models for their presentation. A model of spectral-statistical texture is proposed, which takes into account the random nature of changes in th

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11

Nishad, N., R. Meenakshi, R. Ramakrishnan, and A. Chirputkar. "Texture analysis for skin cancer diagnosis using dermoscopic images." CARDIOMETRY, no. 25 (February 14, 2023): 287–91. http://dx.doi.org/10.18137/cardiometry.2022.25.287-291.

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This paper provides a foundation to examine the dermoscopic images for skin cancer diagnosis. A dermoscopic image will often include textured areas that make up a major amount of the image. It is conceivable to organize and categorize such textures according to whether they are related with artifacts or if they reflect biological structure. Given the connection between structure, disease, and texture, it seems likely that quantitative measurements of texture might make it possible to characterize the tissues included inside a dermoscopic image. It has been shown that texture is a valuable char

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12

Soares, Lucas de Assis, Klaus Fabian Côco, Patrick Marques Ciarelli, and Evandro Ottoni Teatini Salles. "A Class-Independent Texture-Separation Method Based on a Pixel-Wise Binary Classification." Sensors 20, no. 18 (2020): 5432. http://dx.doi.org/10.3390/s20185432.

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Texture segmentation is a challenging problem in computer vision due to the subjective nature of textures, the variability in which they occur in images, their dependence on scale and illumination variation, and the lack of a precise definition in the literature. This paper proposes a method to segment textures through a binary pixel-wise classification, thereby without the need for a predefined number of textures classes. Using a convolutional neural network, with an encoder–decoder architecture, each pixel is classified as being inside an internal texture region or in a border between two di

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13

Abdelmounaime, Safia, and He Dong-Chen. "New Brodatz-Based Image Databases for Grayscale Color and Multiband Texture Analysis." ISRN Machine Vision 2013 (February 24, 2013): 1–14. http://dx.doi.org/10.1155/2013/876386.

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Grayscale and color textures can have spectral informative content. This spectral information coexists with the grayscale or chromatic spatial pattern that characterizes the texture. This informative and nontextural spectral content can be a source of confusion for rigorous evaluations of the intrinsic textural performance of texture methods. In this paper, we used basic image processing tools to develop a new class of textures in which texture information is the only source of discrimination. Spectral information in this new class of textures contributes only to form texture. The textures are

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14

Liu, Changhong, Hongyin Li, Zhongwei Liang, et al. "A Novel Deep-Learning-Based Enhanced Texture Transformer Network for Reference Image Super-Resolution." Electronics 11, no. 19 (2022): 3038. http://dx.doi.org/10.3390/electronics11193038.

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The study explored a deep learning image super-resolution approach which is commonly used in face recognition, video perception and other fields. These generative adversarial networks usually have high-frequency texture details. The relevant textures of high-resolution images could be transferred as reference images to low-resolution images. The latest existing methods use transformer ideas to transfer related textures to low-resolution images, but there are still some problems with channel learning and detailed textures. Therefore, the study proposed an enhanced texture transformer network (E

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15

Volkova, Natalya P., and Viktor N. Krylov. "HYBRID TEXTURE IDENTIFICATION METHOD." Herald of Advanced Information Technology 4, no. 2 (2021): 123–34. http://dx.doi.org/10.15276/hait.02.2021.2.

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The importance of the modeling mode in systems of computer visual pattern recognition is shown. The purpose of the mode is to determine the types of textures that are present on the images processed in intelligent diagnostic systems. Images processed in technical diagnostic systems contain texture regions, which can be represented by different types of textures - spectral, statistical and spectral-statistical. Texture identification methods, such as, statistical, spectral, expert, multifractal, which are used to identify and analyze texture images, have been analyzed. To determine texture regi

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16

Almeghari, Tamara A. I., Mohamed Soufiane Jouini, and Fawaz Hjouj. "Unsupervised texture classification of 3D X-ray Micro-computed Tomography images." Journal of Physics: Conference Series 2701, no. 1 (2024): 012143. http://dx.doi.org/10.1088/1742-6596/2701/1/012143.

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Abstract Characterizing rock proprieties is crucial in the oilfield to evaluate hydrocarbon reserves. Several studies showed a high correlation between rock properties and textures. Therefore, we propose integrating texture information in the images to identify precisely the most representative textures in highly heterogeneous rocks to estimate their properties. First, we implemented a steerable pyramid decomposition to extract the texture features. Then, those parameters were used as input for the Self-organizing map to classify the textures. Finally, by applying several models and comparing

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17

Yang, Junxing, Lu Lu, Ge Peng, He Huang, Jian Wang, and Fei Deng. "Texture-Mapping Error Removal Based on the BRIEF Operator in Image-Based Three-Dimensional Reconstruction." Remote Sensing 15, no. 2 (2023): 536. http://dx.doi.org/10.3390/rs15020536.

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In image-based three-dimensional (3D) reconstruction, texture-mapping techniques can give the model realistic textures. When the geometric surface in some regions is not reconstructed, such as for moving cars, powerlines, and telegraph poles, the textures in the corresponding image are textured to other regions, resulting in errors. To solve this problem, this letter proposes an image consistency detection method based on the Binary Robust Independent Elementary Features (BRIEF) descriptor. The method is composed of two parts. First, each triangle in the mesh and its neighboring triangles are

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18

Dal’Col, Lucas, Daniel Coelho, Tiago Madeira, Paulo Dias, and Miguel Oliveira. "A Sequential Color Correction Approach for Texture Mapping of 3D Meshes." Sensors 23, no. 2 (2023): 607. http://dx.doi.org/10.3390/s23020607.

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Texture mapping can be defined as the colorization of a 3D mesh using one or multiple images. In the case of multiple images, this process often results in textured meshes with unappealing visual artifacts, known as texture seams, caused by the lack of color similarity between the images. The main goal of this work is to create textured meshes free of texture seams by color correcting all the images used. We propose a novel color-correction approach, called sequential pairwise color correction, capable of color correcting multiple images from the same scene, using a pairwise-based method. This

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19

Coelho, Daniel, Lucas Dal’Col, Tiago Madeira, Paulo Dias, and Miguel Oliveira. "A Robust 3D-Based Color Correction Approach for Texture Mapping Applications." Sensors 22, no. 5 (2022): 1730. http://dx.doi.org/10.3390/s22051730.

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Texture mapping of 3D models using multiple images often results in textured meshes with unappealing visual artifacts known as texture seams. These artifacts can be more or less visible, depending on the color similarity between the used images. The main goal of this work is to produce textured meshes free of texture seams through a process of color correcting all images of the scene. To accomplish this goal, we propose two contributions to the state-of-the-art of color correction: a pairwise-based methodology, capable of color correcting multiple images from the same scene; the application of

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20

Wang, Guodong, Zhenkuan Pan, Qian Dong, Ximei Zhao, Zhimei Zhang, and Jinming Duan. "Unsupervised Texture Segmentation Using Active Contour Model and Oscillating Information." Journal of Applied Mathematics 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/614613.

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Textures often occur in real-world images and may cause considerable difficulties in image segmentation. In order to segment texture images, we propose a new segmentation model that combines image decomposition model and active contour model. The former model is capable of decomposing structural and oscillating components separately from texture image, and the latter model can be used to provide smooth segmentation contour. In detail, we just replace the data term of piecewise constant/smooth approximation in CCV (convex Chan-Vese) model with that of image decomposition model-VO (Vese-Osher).

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21

George, Kokkonis, Psannis Kostas, and Asiminidis |. Sotirios Kontogiannis Christodoulos. "Design Tactile Interfaces with Enhanced Depth Images With Patterns and Textures for Visually Impaired People." International Journal of Trend in Scientific Research and Development 3, no. 1 (2018): 1174–78. https://doi.org/10.31142/ijtsrd20210.

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This paper presents the design and development of Tactile Interfaces with Enhanced Images with Patterns and Textures for Visually Impaired People. In particular, haptic interfaces uses a number of predefine tactile texture and patterns to enhance the experience of the tactile feeling of images for visually impaired people. The open source OpenCv application is used to automatically change group of colours from depth images to tactile texture and patterns. The depth images are captured with the he p of RGB Depth cameras. The tactile images are then explored by visually impaired people with the

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22

Xu, Xin, and Yi Wang Chen. "Multifractal-Based Texture Analysis for SAR Images." Advanced Materials Research 915-916 (April 2014): 1216–20. http://dx.doi.org/10.4028/www.scientific.net/amr.915-916.1216.

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SAR images are widely used in land use cover classifications. This paper proposed using multifractal spectrum parameters to analyze texture of SAR images. First multifractal theory and spectrum calculation method were introduced. Multifractal spectrum of a chaos representation was gotten with the method. From the spectrum curve, five parameters were found to describe the curve features. Then the physical meanings of five parameters in multifractal spectra were analyzed. Multifractal spectra of three kinds of textures in a SAR image are calculated, and five parameters are extracted. Finaly we a

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23

Hu, Huiran, and Aiguo Song. "Haptic Texture Rendering of 2D Image Based on Adaptive Fractional Differential Method." Applied Sciences 12, no. 23 (2022): 12346. http://dx.doi.org/10.3390/app122312346.

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The fractional differential algorithm has a good effect on extracting image textures, but it is usually necessary to select an appropriate fractional differential order for textures of different scales, so we propose a novel approach for haptic texture rendering of two-dimensional (2D) images by using an adaptive fractional differential method. According to the fractional differential operator defined by the Grünvald–Letnikov derivative (G–L) and combined with the characteristics of human vision, we propose an adaptive fractional differential method based on the composite sub-band gradient vec

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24

Vijay Kumar, Palnati, Pullela S. V. V. S. R. Kumar, Nakkella Madhuri, and M. Uma Devi. "Stone Image Classification Based on Overlapped 5-bit T-Patterns occurrence on 5-by-5 Sub Images." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 3 (2016): 1152. http://dx.doi.org/10.11591/ijece.v6i3.9233.

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Texture classification is widely used in understanding the visual patterns and has wide range of applications. The present paper derived a novel approach to classify the stone textures based on the patterns occurrence on each sub window. The present approach identifies overlapped nine 5 bit T-patterns (O5TP) on each 5×5 sub window stone image. Based the number of occurrence of T-patterns count the present paper classify the stone images into any of the four classes i.e. brick, granite, marble and mosaic stone images. The novelty of the present approach is that no standard classification algori

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25

Vijay Kumar, Palnati, Pullela S. V. V. S. R. Kumar, Nakkella Madhuri, and M. Uma Devi. "Stone Image Classification Based on Overlapped 5-bit T-Patterns occurrence on 5-by-5 Sub Images." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 3 (2016): 1152. http://dx.doi.org/10.11591/ijece.v6i3.pp1152-1160.

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Texture classification is widely used in understanding the visual patterns and has wide range of applications. The present paper derived a novel approach to classify the stone textures based on the patterns occurrence on each sub window. The present approach identifies overlapped nine 5 bit T-patterns (O5TP) on each 5×5 sub window stone image. Based the number of occurrence of T-patterns count the present paper classify the stone images into any of the four classes i.e. brick, granite, marble and mosaic stone images. The novelty of the present approach is that no standard classification algori

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26

Khan, Haris, Sofiane Mihoubi, Benjamin Mathon, Jean-Baptiste Thomas, and Jon Hardeberg. "HyTexiLa: High Resolution Visible and Near Infrared Hyperspectral Texture Images." Sensors 18, no. 7 (2018): 2045. http://dx.doi.org/10.3390/s18072045.

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We present a dataset of close range hyperspectral images of materials that span the visible and near infrared spectrums: HyTexiLa (Hyperspectral Texture images acquired in Laboratory). The data is intended to provide high spectral and spatial resolution reflectance images of 112 materials to study spatial and spectral textures. In this paper we discuss the calibration of the data and the method for addressing the distortions during image acquisition. We provide a spectral analysis based on non-negative matrix factorization to quantify the spectral complexity of the samples and extend local bin

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Sobus, J., B. Pourdeyhimi, B. Xu, and Y. Ulcay. "Evaluating Loss of Texture Definition in Carpets Using Mathematical Morphology: Covariance." Textile Research Journal 62, no. 1 (1992): 26–39. http://dx.doi.org/10.1177/004051759206200105.

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Carpet textures contain periodic information that varies across constructions and is degraded by mechanical wear. We apply image covariance, a digital implementation of mathematical morphology, to binary carpet images for the purpose of measuring aspects of texture periodicity. Our test materials consist of four kinds of double ply wool carpets of differing textures divided into control, light, and heavy wear samples. Video images were digitized by a True Vision Vista frame grabber. Gray-level images were histogram equalized and converted to binary. Covariance data allow one to measure period

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28

Park, Juan, Chul Min Yeum, and Trevor Hrynyk. "Image Scale Estimation Using Surface Textures for Quantitative Visual Inspection." Journal of Computational Vision and Imaging Systems 6, no. 1 (2021): 1–3. http://dx.doi.org/10.15353/jcvis.v6i1.3541.

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In this study, a learning-based scale estimation technique is proposed to enable quantitative evaluation of inspection regions. The underlying idea is that surface texture of structures (i.e. bridges or buildings) captured on images contains the scale information of the corresponding images, which is represented by pixel per physical dimension (e.g., mm, inch). This allows training a regression model that provides a relationship between surface textures on images and their corresponding scales. Deep convolutional neural network is used to extract scale-related features from the texture patches

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Knill, D. C. "From Contour to Texture: Static Texture Flow is a Strong Cue to Surface Shape." Perception 26, no. 1_suppl (1997): 205. http://dx.doi.org/10.1068/v970082.

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Contours projected from geodesic boundaries of developable surfaces (as are formed by folding and twisting flat surfaces) are particularly salient cues to 3-D surface shape. Textures which are strongly anisotropic (highly oriented) provide a similar source of information. The natural definition of homogeneity for such textures leads to the constraint that the oriented ‘flow’ of texture on a surface follows geodesics of the surface (on average). In the current work, it is shown that the shapes of contours projected from geodesics of developable surfaces, and analogously of oriented texture flow

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Ei, Phyu Win, Mie Tin Mie, and Phyo Thu Pyae. "Texture Images Classification using Secant Lines Segments Histogram." International Journal of Trend in Scientific Research and Development 3, no. 5 (2019): 2607–9. https://doi.org/10.5281/zenodo.3591769.

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Texture classification is the process to classify different textures from the given images. The aim of texture classification is to classify the category of a texture image. To design an effective algorithm for texture classification, it is essential to find a set of texture features with good discriminating power. This paper presents a texture classification system using secant lines segments histogram and Euclidean Distance. Secant lines segments histogram is used to generate the features from texture images as a histogram. These features offer a better discriminating strategy for texture cl

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31

Zheng, Lin, Wang Chenghao, Li Zichao, Wang Zhuoyue, Liu Xinqi, and Zhu Yue. "Neural Radiance Fields Convert 2D to 3D Texture." Applied Science and Biotechnology Journal for Advanced Research 3, no. 3 (2024): 40–44. https://doi.org/10.5281/zenodo.12200107.

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The objective of our project is to capture pictures or videos by surrounding a circle of objects, such as chairs, tables, cars, and more.[1]Utilizing advanced 3D reconstruction technology, we aim to generate 3D models of these captured objects. Post reconstruction, these 3D models can be edited through an intuitive interface, enabling users to apply different textures and make other modifications. This project has significant applications in various domains such as home decoration, vehicle customization, and beyond. For the 3D reconstruction in this project, we employed Nvidia's latest ngp-ins

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32

Li, You Jiao, Tong Sheng Ju, and Meng Gao. "Texture Classification of 3D Surface Textures via Directional Quincunx Lifting." Applied Mechanics and Materials 686 (October 2014): 82–85. http://dx.doi.org/10.4028/www.scientific.net/amm.686.82.

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This thesis presents a new approach to classify 3D surface textures by using lifting transform with quincunx subsampling. Feature vectors are generated from eight different lifting prediction directions. We classify 3D surface texture images based on minimum Euclidean distance between the test images and the training sets. The feasibility and effectiveness of our proposed approach can be validated by the experimental results.

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Hu, Shirui, Zhiyuan Li, Shaohua Wang, Mingyao Ai, and Qingwu Hu. "A Texture Selection Approach for Cultural Artifact 3D Reconstruction Considering Both Geometry and Radiation Quality." Remote Sensing 12, no. 16 (2020): 2521. http://dx.doi.org/10.3390/rs12162521.

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3D reconstruction of culture artifacts has great potential in digital heritage documentation and protection. Choosing the proper images for texture mapping from multi-view images is a major challenge for high precision and high quality 3D reconstruction of culture artifacts. In this study, a texture selection approach, considering both the geometry and radiation quality for 3D reconstruction of cultural artifacts while using multi-view dense matching is proposed. First, a Markov random field (MRF) method is presented to select images from the best angle of view among texture image sets. Then,

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34

Kinge, Sanjaykumar, B. Sheela Rani, and Mukul Sutaone. "Restored texture segmentation using Markov random fields." Mathematical Biosciences and Engineering 20, no. 6 (2023): 10063–89. http://dx.doi.org/10.3934/mbe.2023442.

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<abstract> <p>Texture segmentation plays a crucial role in the domain of image analysis and its recognition. Noise is inextricably linked to images, just like it is with every signal received by sensing, which has an impact on how well the segmentation process performs in general. Recent literature reveals that the research community has started recognizing the domain of noisy texture segmentation for its work towards solutions for the automated quality inspection of objects, decision support for biomedical images, facial expressions identification, retrieving image data from a hug

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Anjaiah, P., K. Rajendra Prasad, and C. Raghavendra. "Effective Texture Features for Segmented Mammogram Images." International Journal of Engineering & Technology 7, no. 3.12 (2018): 666. http://dx.doi.org/10.14419/ijet.v7i3.12.16450.

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Textures of mammogram images are useful for finding masses or cancer cases in mammography, which has been used by radiologist. Textures are greatly succeed for segmented images rather than normal images. It is necessary to perform segmentation for exclusive specification of cancer and non-cancer regions separately. Region of interest (ROI) in most commonly used technique for mammogram segmentation. Limitation of this method is that it unable to explore segmentation for large collection of mammogram images. Therefore, this paper is proposed multi-ROI segmentation for addressing the above limita

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36

Chen, Fei, and Jaeho Choi. "ATGT3D: Animatable Texture Generation and Tracking for 3D Avatars." Electronics 13, no. 22 (2024): 4562. http://dx.doi.org/10.3390/electronics13224562.

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We propose the ATGT3D an Animatable Texture Generation and Tracking for 3D Avatars, featuring the innovative design of the Eye Diffusion Module (EDM) and Pose Tracking Diffusion Module (PTDM), which are dedicated to high-quality eye texture generation and synchronized tracking of dynamic poses and textures, respectively. Compared to traditional GAN and VAE methods, ATGT3D significantly enhances texture consistency and generation quality in animated scenes using the EDM, which produces high-quality full-body textures with detailed eye information using the HUMBI dataset. Additionally, the Pose

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37

Zhou, Xufeng, Junhui Lu, Yuechi Yu, and Zhenghang Yi. "Study on the Influence of Asphalt Pavement Texture on Drainage Performance." ce/papers 8, no. 2 (2025): 1621–28. https://doi.org/10.1002/cepa.3247.

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AbstractDuring rainy weather, water films on road surfaces can reduce skid resistance, leading to hydroplaning and traffic accidents. This study involves collecting images of asphalt pavement and processing these images using image processing techniques to obtain the texture occupancy of the recessed areas of the pavement. To eliminate noise in the asphalt pavement images and make edge features more distinct, the preprocessing steps include grayscaling, image de‐noising, and image enhancement. Threshold segmentation is then used to obtain binary images of the asphalt pavement, and contour dete

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38

Akl, Adib. "Adaptation of Symmetric Positive Semi-Definite Matrices for the Analysis of Textured Images." Cybernetics and Information Technologies 18, no. 1 (2018): 51–68. http://dx.doi.org/10.2478/cait-2018-0005.

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Abstract This paper addresses the analysis of textured images using the symmetric positive semi-definite matrix. In particular, a field of symmetric positive semi-definite matrices is used to estimate the structural information represented by the local orientation and the degree of anisotropy in structured and sinusoid-like textured images. In order to ensure faithful local structure estimation, an adaptive algorithm for the regularization of the extent of gradient fields smoothing is proposed. Results obtained on different texture samples show the strength of the proposed method in accurately

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Hao, Xinjie, Jiahui Wang, Wei Leng, Rongting Zhang, and Guangyun Zhang. "MFSM-Net: Multimodal Feature Fusion for the Semantic Segmentation of Urban-Scale Textured 3D Meshes." Remote Sensing 17, no. 9 (2025): 1573. https://doi.org/10.3390/rs17091573.

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The semantic segmentation of textured 3D meshes is a critical step in constructing city-scale realistic 3D models. Compared to colored point clouds, textured 3D meshes have the advantage of high-resolution texture image patches embedded on each mesh face. However, existing studies predominantly focus on their geometric structures, with limited utilization of these high-resolution textures. Inspired by the binocular perception of humans, this paper proposes a multimodal feature fusion network based on 3D geometric structures and 2D high-resolution texture images for the semantic segmentation of

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Dong, Junyu, Jun Liu, Kang Yao, et al. "Survey of Procedural Methods for Two-Dimensional Texture Generation." Sensors 20, no. 4 (2020): 1135. http://dx.doi.org/10.3390/s20041135.

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Textures are the most important element for simulating real-world scenes and providing realistic and immersive sensations in many applications. Procedural textures can simulate a broad variety of surface textures, which is helpful for the design and development of new sensors. Procedural texture generation is the process of creating textures using mathematical models. The input to these models can be a set of parameters, random values generated by noise functions, or existing texture images, which may be further processed or combined to generate new textures. Many methods for procedural textur

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41

You, Boyang, and Barmak Honarvar Shakibaei Asli. "A Model Development Approach Based on Point Cloud Reconstruction and Mapping Texture Enhancement." Big Data and Cognitive Computing 8, no. 11 (2024): 164. http://dx.doi.org/10.3390/bdcc8110164.

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To address the challenge of rapid geometric model development in the digital twin industry, this paper presents a comprehensive pipeline for constructing 3D models from images using monocular vision imaging principles. Firstly, a structure-from-motion (SFM) algorithm generates a 3D point cloud from photographs. The feature detection methods scale-invariant feature transform (SIFT), speeded-up robust features (SURF), and KAZE are compared across six datasets, with SIFT proving the most effective (matching rate higher than 0.12). Using K-nearest-neighbor matching and random sample consensus (RAN

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Chaudhary, R., RK Pandey, and SK Mazumdar. "Tribological studies of low and high viscous oils lubricated heavily loaded textured point contacts under the reciprocating motion." Proceedings of the Institution of Mechanical Engineers, Part J: Journal of Engineering Tribology 234, no. 2 (2019): 229–46. http://dx.doi.org/10.1177/1350650119858240.

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The tribo-performance behaviors of lubricated textured point contacts have been explored herein at relatively high contact loads (up to 3 GPa) under reciprocating motion (0.2 and 0.4 m/s) employing low (ν@40 ℃ = 100 cSt) and high (ν@40 ℃ = 422 cSt) viscous oils. In this experimental study, two contacts (flat conventional surface vs. polished ball and textured flat surface vs. polished ball surface) have been created for the investigations of friction, wear, and contact potential (ability for film formation). It is found that in the presence of texture at the concentrated contacts, the coeffici

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Qiao, Shuang, Jia Ning Sun, Jian Li, and Ji Peng Huang. "A Novel Texture Extraction Method for Digital Radiography." Applied Mechanics and Materials 719-720 (January 2015): 1148–54. http://dx.doi.org/10.4028/www.scientific.net/amm.719-720.1148.

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As known, there always exist severely degradation problems in digital radiography. How we can extract necessary textures from degraded radiographic images is the post-processing key. Local binary pattern (LBP) is a well-known method, which is widely used in fast image texture extraction. However, for noisy images, LBP can’t work well due to its sensitivity to details. On the other hand, as one of the important shock filters developed in recent years, complex shock filter possesses excellent capabilities in textural image processing. Here, by combining complex shock filter with LBP, a novel fas

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Ropelewska, Ewa. "The application of image processing for cultivar discrimination of apples based on texture features of the skin, longitudinal section and cross-section." European Food Research and Technology 247, no. 5 (2021): 1319–31. http://dx.doi.org/10.1007/s00217-021-03711-3.

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AbstractThe study was aimed at the evaluation of the usefulness of textures of the outer surface from the images of apple skin and flesh for discrimination of different cultivars. The texture parameters were calculated from color channels: R, G, B, L, a, b, U, V, H, S, I, X, Y, Z. In the case of cultivar discrimination performed for the apple skin, the highest accuracies were obtained for textures from channels R, a and X. In the case of channels R and a, the apples were classified with the total accuracy of up to 93%. For channel X, the highest total accuracy was 90%. For discrimination based

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Chen, Jinsong, Hu Han, and Shiguang Shan. "Towards High-Fidelity Face Self-Occlusion Recovery via Multi-View Residual-Based GAN Inversion." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 1 (2022): 294–302. http://dx.doi.org/10.1609/aaai.v36i1.19905.

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Face self-occlusions are inevitable due to the 3D nature of the human face and the loss of information in the projection process from 3D to 2D images. While recovering face self-occlusions based on 3D face reconstruction, e.g., 3D Morphable Model (3DMM) and its variants provides an effective solution, most of the existing methods show apparent limitations in expressing high-fidelity, natural, and diverse facial details. To overcome these limitations, we propose in this paper a new generative adversarial network (MvInvert) for natural face self-occlusion recovery without using paired image-text

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Chen, L. C., L. L. Chan, and W. C. Chang. "INTEGRATION OF IMAGES AND LIDAR POINT CLOUDS FOR BUILDING FAÇADE TEXTURING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 8, 2016): 379–82. http://dx.doi.org/10.5194/isprs-archives-xli-b2-379-2016.

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This paper proposes a model-based method for texture mapping using close-range images and Lidar point clouds. Lidar point clouds are used to aid occlusion detection. For occluded areas, we compensate the occlusion by different view-angle images. Considering the authenticity of façade with repeated patterns under different illumination conditions, a selection of optimum pattern is suggested. In the selection, both geometric shape and texture are analyzed. The grey level co-occurrence matrix analysis is applied for the selection of the optimal façades texture to generate of photorealistic buildi

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47

Chen, L. C., L. L. Chan, and W. C. Chang. "INTEGRATION OF IMAGES AND LIDAR POINT CLOUDS FOR BUILDING FAÇADE TEXTURING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 8, 2016): 379–82. http://dx.doi.org/10.5194/isprsarchives-xli-b2-379-2016.

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This paper proposes a model-based method for texture mapping using close-range images and Lidar point clouds. Lidar point clouds are used to aid occlusion detection. For occluded areas, we compensate the occlusion by different view-angle images. Considering the authenticity of façade with repeated patterns under different illumination conditions, a selection of optimum pattern is suggested. In the selection, both geometric shape and texture are analyzed. The grey level co-occurrence matrix analysis is applied for the selection of the optimal façades texture to generate of photorealistic buildi

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48

Goyal, Aparna, and Reena Gunjan. "Bleeding Detection in Gastrointestinal Images using Texture Classification and Local Binary Pattern Technique: A Review." E3S Web of Conferences 170 (2020): 03007. http://dx.doi.org/10.1051/e3sconf/202017003007.

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Texture analysis has proven to be a breakthrough in many applications of computer image analysis. It has been used for classification or segmentation of images which requires an effective description of image texture. Due to high discriminative power and simplicity of computation, the local binary pattern descriptors have been used for distinguishing different textures and in extracting texture and color in medical images. This paper discusses performance of various texture classification techniques using Contourlet Transform, Discrete Fourier Transform, Local Binary Patterns and Lacunarity an

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Suresh Kumar, R., and A. R. Mahesh Balaji. "Land use land cover classification using local multiple pattern from very high resolution satellite imagery." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 971–76. http://dx.doi.org/10.5194/isprsarchives-xl-8-971-2014.

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The recent development in satellite sensors provide images with very high spatial resolution that aids detailed mapping of Land Use Land Cover (LULC). But the heterogeneity in the landscapes often results in spectral variation within the same and spectral confusion among different LU/LC classes at finer spatial resolution. This leads to poor classification performances based on traditional spectral-based classification. Many studies have been addressed to improve this classification by incorporating texture information with multispectral images. Although different methods are available to extr

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Abramov, Aleksei, Sergej M. Bobrovskij, Nikolay Nosov, Vladimir Tabakov, and Fanyusa Lopatina. "Method for Determining Texture Parameters of Processed Precision Surfaces by Correlation." Key Engineering Materials 822 (September 2019): 731–36. http://dx.doi.org/10.4028/www.scientific.net/kem.822.731.

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The article describes a new method for texture analysis of precision machined surfaces, which is based on the use of computer optics and an autocorrelation method for processing the obtained images of the textures of the studied microreliefs. The method is based on a probabilistic comparative assessment of the unknown texture of the studied microrelief with known textures of the reference microreliefs, for which the parameters of the microreliefs are predetermined according to the state standards of the Russian Federation.

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