Articoli di riviste: "Textured images"

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Oliveira, Miguel, Gi-Hyun Lim, Tiago Madeira, Paulo Dias e Vítor Santos. "Robust Texture Mapping Using RGB-D Cameras". Sensors 21, n. 9 (7 maggio 2021): 3248. http://dx.doi.org/10.3390/s21093248.

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Abstract (sommario):

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, capable of producing quality textures even in considerable camera misalignments scenarios. To this end, we argue that use of the depth data from RGB-D images can be an invaluable help to confer such robustness to the texture mapping process. Results show that the complete texture mapping procedure proposed in this paper is able to significantly improve the quality of the produced textured 3D meshes.

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Hemalatha, S., e 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, n. 2 (luglio 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 texture feature is analogous to edges and thus, the time complexity is reduced significantly. The model proposed in this work is based on Gaussian kernel smoothing, Fractional partial derivatives and a statistical approach. It is justified to be robust to noisy images and possesses statistical interpretation. The model is validated by the classification experiments on different types of textured images from Brodatz album. It achieves higher classification accuracy than the existing methods.

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Dal’Col, Lucas, Daniel Coelho, Tiago Madeira, Paulo Dias e Miguel Oliveira. "A Sequential Color Correction Approach for Texture Mapping of 3D Meshes". Sensors 23, n. 2 (5 gennaio 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 approach consists of sequentially color correcting each image of the set with respect to a reference image, following color-correction paths computed from a weighted graph. The color-correction algorithm is integrated with a texture-mapping pipeline that receives uncorrected images, a 3D mesh, and point clouds as inputs, producing color-corrected images and a textured mesh as outputs. Results show that the proposed approach outperforms several state-of-the-art color-correction algorithms, both in qualitative and quantitative evaluations. The approach eliminates most texture seams, significantly increasing the visual quality of the textured meshes.

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Bhaumik, Shubrajit, Viorel Paleu, Dhrubajyoti Chowdhury, Adarsh Batham, Udit Sehgal, Basudev Bhattacharya, Chiradeep Ghosh e Shubhabrata Datta. "Tribological Investigation of Textured Surfaces in Starved Lubrication Conditions". Materials 15, n. 23 (27 novembre 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 network (ANN) model, predicting the influence of the surface texture as a function of the load, depth of cut and distance between the micro-textures.

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Coelho, Daniel, Lucas Dal’Col, Tiago Madeira, Paulo Dias e Miguel Oliveira. "A Robust 3D-Based Color Correction Approach for Texture Mapping Applications". Sensors 22, n. 5 (23 febbraio 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 3D information from the scene, namely meshes and point clouds, to build a filtering procedure, in order to produce a more reliable spatial registration between images, thereby increasing the robustness of the color correction procedure. We also present a texture mapping pipeline that receives uncorrected images, an untextured mesh, and point clouds as inputs, producing a final textured mesh and color corrected images as output. Results include a comparison with four other color correction approaches. These show that the proposed approach outperforms all others, both in qualitative and quantitative metrics. The proposed approach enhances the visual quality of textured meshes by eliminating most of the texture seams.

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Akl, Adib. "Adaptation of Symmetric Positive Semi-Definite Matrices for the Analysis of Textured Images". Cybernetics and Information Technologies 18, n. 1 (1 marzo 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 representing the local variation of orientations in the underlying textured images, which paves the way towards an accurate analysis of the texture structures.

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Beschastnov, Nikolay P., Irina V. Rybaulina e Evdokia N. Dergileva. "FACTURE, TEXTURE AND TEHNO-ORNAMENT IN MODERN DESIGN: FUNCTION AND ARTISTIC MEANING". Technologies & Quality 51, n. 1 (29 aprile 2021): 40–45. http://dx.doi.org/10.34216/2587-6147-2021-1-51-40-45.

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The article is devoted to defining the place and role of textured formations and techno-ornament in modern design, setting out the features of their use and methods of obtaining. The sources of the artistic attitude to the texture and texture of the material in the creation of works of decorative and applied art, interiors are briefly outlined, the importance of increased attention to them in the modern period is revealed. A special role is assigned to techno-ornamentation, which has arisen in high-tech culture and has become an exponent of new rhythmic-plastic images that are in tune with modernity. Images with machine aesthetics with alternating elements that do not have open semantic content. The authors came to the conclusion that in the late 20 th to the early 21 st centuries there was an unprecedented increase in interest in textured and textural ornamental formations. Their images are very vague and associated with an environment largely distanced from humans. Ornament in such an environment is extremely contextual.

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Barburiceanu, Stefania, Romulus Terebes e Serban Meza. "3D Texture Feature Extraction and Classification Using GLCM and LBP-Based Descriptors". Applied Sciences 11, n. 5 (5 marzo 2021): 2332. http://dx.doi.org/10.3390/app11052332.

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Lately, 3D imaging techniques have achieved a lot of progress due to recent developments in 3D sensor technologies. This leads to a great interest regarding 3D image feature extraction and classification techniques. As pointed out in literature, one of the most important and discriminative features in images is the textural content. Within this context, we propose a texture feature extraction technique for volumetric images with improved discrimination power. The method could be used in textured volumetric data classification tasks. To achieve this, we fuse two complementary pieces of information, feature vectors derived from Local Binary Patterns (LBP) and the Gray-Level Co-occurrence Matrix-based methods. They provide information regarding the image pattern and the contrast, homogeneity and local anisotropy in the volumetric data, respectively. The performance of the proposed technique was evaluated on a public dataset consisting of volumetric textured images affected by several transformations. The classifiers used are the Support Vector Machine, k-Nearest Neighbours and Random Forest. Our method outperforms other handcrafted 3D or 2D texture feature extraction methods and typical deep-learning networks. The proposed technique improves the discrimination power and achieves promising results even if the number of images per class is relatively small.

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Wen, Mingyun, Jisun Park e Kyungeun Cho. "Textured Mesh Generation Using Multi-View and Multi-Source Supervision and Generative Adversarial Networks". Remote Sensing 13, n. 21 (22 ottobre 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 network is like that of a generative adversarial network comprising a generator and a discriminator. During the training of the texture-reconstruction network, the discriminator must focus on learning high-quality texture predictions and to ignore the difference between the generated mesh and the actual mesh. To achieve this objective, we used meshes reconstructed using the mesh-reconstruction network and textures generated through inverse rendering to generate pseudo-ground-truth images. We conducted experiments using the 3D-Future dataset, and the results prove that our proposed approach can be used to generate improved three-dimensional (3D) textured meshes compared to existing methods, both quantitatively and qualitatively. Additionally, through our proposed approach, the texture of the output image is significantly improved.

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Gimel'Farb, Georgy L., e Anil K. Jain. "On retrieving textured images from an image database". Pattern Recognition 29, n. 9 (settembre 1996): 1461–83. http://dx.doi.org/10.1016/0031-3203(96)00011-8.

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Nishad, N., R. Meenakshi, R. Ramakrishnan e A. Chirputkar. "Texture analysis for skin cancer diagnosis using dermoscopic images". CARDIOMETRY, n. 25 (14 febbraio 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 characteristic for the characterization of skin cancer in dermoscopic images. The proposed system is comprised of two stages: the first is the extraction of information or features from dermoscopic images, and the second is the categorization of those images using a decision tree classifier. Based on the findings, it is possible to draw the conclusion that the extracted features have kept all of the information presents in the dermoscopic image that provides an overall accuracy of 98.89%

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Lehmann, F. "Turbo Segmentation of Textured Images". IEEE Transactions on Pattern Analysis and Machine Intelligence 33, n. 1 (gennaio 2011): 16–29. http://dx.doi.org/10.1109/tpami.2010.58.

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Park, Jaehyun, e Ludwik Kurz. "Unsupervised segmentation of textured images". Information Sciences 92, n. 1-4 (luglio 1996): 255–76. http://dx.doi.org/10.1016/0020-0255(96)00047-3.

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Otazu, Xavier, e Maria Vanrell. "Perceptual Representation of Textured Images". Journal of Imaging Science and Technology 49, n. 3 (1 luglio 2005): 262–71. http://dx.doi.org/10.2352/j.imagingsci.technol.2005.49.3.art00007.

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Rao, K. Subba, P. Sammulal, M. Sambasivarao e V. Sathyamoorthy. "Hybrid Image Classification using ACO with Fuzzy Logic for Textured and Non-Textured Images". Indian Journal of Science and Technology 10, n. 14 (1 aprile 2017): 1–5. http://dx.doi.org/10.17485/ijst/2017/v10i14/106380.

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Lai, Jiing-Yih, Tsung-Chien Wu, Watchama Phothong, Douglas Wang, Chao-Yaug Liao e Ju-Yi Lee. "A High-Resolution Texture Mapping Technique for 3D Textured Model". Applied Sciences 8, n. 11 (12 novembre 2018): 2228. http://dx.doi.org/10.3390/app8112228.

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Abstract (sommario):

We proposed a texture mapping technique that comprises mesh partitioning, mesh parameterization and packing, texture transferring, and texture correction and optimization for generating a high-quality texture map of a three-dimensional (3D) model for applications in e-commerce presentations. The main problems in texture mapping are that the texture resolution is generally worse than in the original images and considerable photo inconsistency exists at the transition of different image sources. To improve the texture resolution, we employed an oriented boundary box method for placing mesh islands on the parametric (UV) map. We also provided a texture size that can keep the texture resolution of the 3D textured model similar to that of the object images. To improve the photo inconsistency problem, we employed a method to detect and overcome the missing color that might exist on a texture map. We also proposed a blending process to minimize the transition error caused by different image sources. Thus, a high-quality 3D textured model can be obtained by applying this series of processes for presentations in e-commerce.

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Kang, Junhua, Fei Deng, Xinwei Li e 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 (3 giugno 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 images for photorealistic visualization. Our approach include three major steps as follows: mesh parameterization, texture atlas generation and texture blending. Firstly, mesh parameterization procedure referring to mesh segmentation and mesh unfolding is performed to reduce geometric distortion in the process of mapping 2D texture to 3D model. Secondly, in the texture atlas generation step, the texture of each segmented region in texture domain is reconstructed from all visible images with exterior orientation and interior orientation parameters. Thirdly, to avoid color discontinuities at boundaries between texture regions, the final texture map is generated by blending texture maps from several corresponding images. We evaluated our texture reconstruction framework on a dataset of a city. The resulting mesh model can get textured by created texture without resampling. Experiment results show that our method can effectively mitigate the occurrence of texture fragmentation. It is demonstrated that the proposed framework is effective and useful for automatic texture reconstruction of 3D city model.

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Kang, Junhua, Fei Deng, Xinwei Li e 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 (3 giugno 2016): 341–47. http://dx.doi.org/10.5194/isprs-archives-xli-b1-341-2016.

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Abstract (sommario):

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 images for photorealistic visualization. Our approach include three major steps as follows: mesh parameterization, texture atlas generation and texture blending. Firstly, mesh parameterization procedure referring to mesh segmentation and mesh unfolding is performed to reduce geometric distortion in the process of mapping 2D texture to 3D model. Secondly, in the texture atlas generation step, the texture of each segmented region in texture domain is reconstructed from all visible images with exterior orientation and interior orientation parameters. Thirdly, to avoid color discontinuities at boundaries between texture regions, the final texture map is generated by blending texture maps from several corresponding images. We evaluated our texture reconstruction framework on a dataset of a city. The resulting mesh model can get textured by created texture without resampling. Experiment results show that our method can effectively mitigate the occurrence of texture fragmentation. It is demonstrated that the proposed framework is effective and useful for automatic texture reconstruction of 3D city model.

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Volkova, Natalya P., e Viktor N. Krylov. "VECTOR-DIFFERENCE TEXTURE SEGMENTATION METHOD IN TECHNICAL AND MEDICAL EXPRESS DIAGNOSTIC SYSTEMS". Herald of Advanced Information Technology 3, n. 4 (20 novembre 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 the field variations and quasi-harmonics. On its basis, a vector-difference method of texture segmentation has been developed, which is based on the vector transformation of images of spectral and statistical textures based on vector algebra. The stages of the vector-difference method are the following: an evaluation of the spectral texture feature; an evaluation of the statistical texture feature; vector-difference transformation of texture images; a boundary detection of the homogeneous regions. For each pixel of the image in the processing aperture, the features of the spectral and statistical texture are evaluated. Statistical texture evaluation was performed by the quadratic-amplitude transformation. At the stage of vector-difference transformation of texture images, a vector of features of each pixel of an image is constructed, the elements of which are estimates of features of a spectral and statistical texture, and the modulus of the difference of two vectors is calculated. At the stage of boundary detection of homogeneous regions, Canny method was applied. The developed vector-difference texture segmentation method was applied both to model images of spectral-statistical texture and to texture images obtained in technical and medical diagnostics systems, namely, for images of psoriasis disease and wear zones of cutting tools. To compare the segmentation results, frequency-detector and amplitude-detector methods of texture segmentation were applied to these images. The quality of segmentation of homogeneous textured regions was evaluated by the Pratt's criterion and by constructing a confusion matrix. The research results showed that the developed vector-difference texture segmentation method has increased noise tolerance at a sufficient processing speed.

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Fu, Ying, Xiaohua Li, Lei Liang, Yi Zhang e Jiliu Zhou. "The Restoration of Textured Images Using Fractional-Order Regularization". Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/356906.

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Image restoration problem is ill-posed, so most image restoration algorithms exploit sparse prior in gradient domain to regularize it to yield high-quality results, reconstructing an image with piecewise smooth characteristics. While sparse gradient prior has good performance in noise removal and edge preservation, it also tends to remove midfrequency component such as texture. In this paper, we introduce the sparse prior in fractional-order gradient domain as texture-preserving strategy to restore textured images degraded by blur and/or noise. And we solve the unknown variables in the proposed model using method based on half-quadratic splitting by minimizing the nonconvex energy functional. Numerical experiments show our algorithm's robust outperformance.

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Park, Chang-Min, e Chang-Geun Kim. "Automatic Segmentation for Textured Object Images". International Journal of Multimedia and Ubiquitous Engineering 9, n. 9 (30 settembre 2016): 93–100. http://dx.doi.org/10.14257/ijmue.2016.11.9.10.

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Bouman, C., e B. Liu. "Multiple resolution segmentation of textured images". IEEE Transactions on Pattern Analysis and Machine Intelligence 13, n. 2 (1991): 99–113. http://dx.doi.org/10.1109/34.67641.

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Jain, Palak, e Umesh Ghanekar. "Robust watermarking technique for textured images". Procedia Computer Science 125 (2018): 179–86. http://dx.doi.org/10.1016/j.procs.2017.12.025.

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Li, Fang, Chaomin Shen, Chunli Shen e Guixu Zhang. "Variational denoising of partly textured images". Journal of Visual Communication and Image Representation 20, n. 4 (maggio 2009): 293–300. http://dx.doi.org/10.1016/j.jvcir.2009.01.003.

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Wu, Hai-Shan, Joseph Barba e Joan Gil. "Morphological Segmentation of Textured Cell Images". Journal of Imaging Science and Technology 40, n. 3 (1 maggio 1996): 265–70. http://dx.doi.org/10.2352/j.imagingsci.technol.1996.40.3.art00013.

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Salem, Amr, Hussien Hegab e Hossam A. Kishawy. "Experimental Investigation of the Derivative Cutting When Machining AISI 1045 with Micro-Textured Cutting Tools". Metals 13, n. 9 (13 settembre 2023): 1587. http://dx.doi.org/10.3390/met13091587.

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Abstract (sommario):

In the context of satisfying sustainability requirements nowadays, dry machining is one of the ideal strategies to eliminate the environmental and human health burdens of machining processes. In addition, micro-textured cutting tools are used to improve the performance of dry machining processes. Micro-textures reduce the chip-tool contact length and thus reduce friction and heat, which results in fewer cutting forces and temperature. However, the action of micro-cutting of the bottom side of the chip, which is known as derivative cutting, cuts down the gains of using textured tools, where derivative cutting leads to higher cutting forces, heat, and tool wear. This study aimed to investigate the effects of significant texture design parameters (i.e., micro-groove width) when cutting AISI 1045 steel using different machining parameters (i.e., 75 m/min and 150 m/min of cutting velocity, 0.05 and 0.10 mm/rev of feed). Three different textured cutting tool designs were prepared using the laser texturing technique and then utilized in machining experiments. In addition, the measured machining outputs were forces, power consumption, flank wear, and surface roughness. There were no marks for the derivative cutting when using the textured cutting tool with the narrowest micro-grooves according to the obtained microscopical images after the machining tests. In addition, the textured cutting tool, which included the narrowest micro-grooves, showed better performance compared to the non-textured cutting tool and the other textured tool designs in terms of cutting and feed forces, power consumption, flank tool wear, and surface roughness at the used cutting conditions. This confirmed that the careful optimal design of the micro-textured tools can reduce or eliminate the severity of the derivative cutting, and thus improve the overall machining performance.

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Kasparis, T., D. Charalampidis, M. Georgiopoulos e J. Rolland. "Segmentation of textured images based on fractals and image filtering". Pattern Recognition 34, n. 10 (ottobre 2001): 1963–73. http://dx.doi.org/10.1016/s0031-3203(00)00126-6.

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Yang, Junxing, Lu Lu, Ge Peng, He Huang, Jian Wang e Fei Deng. "Texture-Mapping Error Removal Based on the BRIEF Operator in Image-Based Three-Dimensional Reconstruction". Remote Sensing 15, n. 2 (16 gennaio 2023): 536. http://dx.doi.org/10.3390/rs15020536.

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Abstract (sommario):

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 sampled uniformly to obtain sampling points. Then, these sampled points are projected into the visible image of the triangle, and the corresponding sampled points and their RGB color values are obtained on the corresponding image. Based on the sampled points on these images, a BRIEF descriptor is calculated for each image corresponding to that triangle. In the second step, the Hamming distance between these BRIEF descriptors is calculated, outliers are removed according to the method, and noisy images are also removed. In addition, we propose adding semantic information to Markov energy optimization to reduce errors further. The two methods effectively reduced errors in texture mapping caused by objects not reconstructed, improving the texture quality of 3D models.

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Chaudhary, R., RK Pandey e 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, n. 2 (25 giugno 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 coefficient of friction and wear have reduced considerably with high viscous oil irrespective of operating parameters. However, low viscous oil has yielded an increase in the wear under identical operating parameters. The contact potential (an indirect indication of film formation during the running-in period) in the presence of texture develops rapidly as compared to the conventional surface with both oils. It has demonstrated a reduction in the running-in period in the presence of textures at the contacts. The optical microscope images of worn surfaces of balls and tracks have also been presented for the quantification of wear and understanding of the associated mechanisms.

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Casaca, Wallace, Maurílio Boaventura, Marcos Proença de Almeida e Luis Gustavo Nonato. "Combining anisotropic diffusion, transport equation and texture synthesis for inpainting textured images". Pattern Recognition Letters 36 (gennaio 2014): 36–45. http://dx.doi.org/10.1016/j.patrec.2013.08.023.

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Davydova, K., G. Kuschk, L. Hoegner, P. Reinartz e U. Stilla. "CONSISTENT MULTI-VIEW TEXTURING OF DETAILED 3D SURFACE MODELS". ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W4 (11 marzo 2015): 25–31. http://dx.doi.org/10.5194/isprsannals-ii-3-w4-25-2015.

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Abstract (sommario):

Texture mapping techniques are used to achieve a high degree of realism for computer generated large-scale and detailed 3D surface models by extracting the texture information from photographic images and applying it to the object surfaces. Due to the fact that a single image cannot capture all parts of the scene, a number of images should be taken. However, texturing the object surfaces from several images can lead to lighting variations between the neighboring texture fragments. In this paper we describe the creation of a textured 3D scene from overlapping aerial images using a Markov Random Field energy minimization framework. We aim to maximize the quality of the generated texture mosaic, preserving the resolution from the original images, and at the same time to minimize the seam visibilities between adjacent fragments. As input data we use a triangulated mesh of the city center of Munich and multiple camera views of the scene from different directions.

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Berezina, S. I., Yu O. Gordienko e O. I. Solonets. "ANALYSIS OF WAYS OF SOLVING THE SEGMENTATION PROBLEM FOR HIGHLY TEXTURED OBJECTS". Проблеми створення, випробування, застосування та експлуатації складних інформаційних систем, n. 17 (30 dicembre 2019): 27–40. http://dx.doi.org/10.46972/2076-1546.2019.17.03.

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Increment of speed and reliability of aerospace images processing is directly related to solution of the task of automation of images interpretation process, which is achieved by minimizing search areas, detecting masked objects and defining the dynamics of changes in surveillance areas. The primary stage that in general determines the quality of results received by automated processing and interpretation is thematic segmentation of the image. In the process of thematic segmentation it is necessary to take into account presence of a large number of textured objects. The paper analyzes the ways of solving the segmentation problem for highly textured objects with large range of variation of possible color values. The research included separation of woodlands and single plants from meadows, steppes, etc., which are characterized by similar color characteristics, but differ in texture. It also included separation of residential areas from forests, which are characterized by the same grain size of texture and different color characteristics. The method of texture description, which is based on calculation of the number of differences in brightness per unit area of the image, the method of description and measurement of texture, characterized by the length of the series, the methods of texture description based on calculation of their fractal dimension have been investigated. In order to describe the texture by different methods, first of all, an aperture of the analysis window was defined. That aperture ensures separation of different classes of objects. The analyzed methods of texture description showed that areas of false identification are always present in the result images. It was determined that the best results were obtained with two of the discussed methods. The first one was the method of texture description and measurement based on calculation of the number of brightness differences per unit area of the image. The second one was the method of texture description based on calculation of fractal dimension by searching the area of the pyramid which covers image fragments. To obtain a more accurate segmented map of an image containing highly textured fragments, a combination of the two methods is suggested.

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sandhu, Tajman. "Domain Specific CBIR for Highly Textured Images". Computer Science & Engineering: An International Journal 3, n. 2 (30 aprile 2013): 33–39. http://dx.doi.org/10.5121/cseij.2013.3203.

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Wu, H. S., J. Barba e J. Gil. "Region growing segmentation of textured cell images". Electronics Letters 32, n. 12 (1996): 1084. http://dx.doi.org/10.1049/el:19960738.

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Zhang, Zhe, Panpan Xu, Jian Chang, Wencheng Wang, Chong Zhao e Jian Jun Zhang. "Generating High‐quality Superpixels in Textured Images". Computer Graphics Forum 39, n. 7 (ottobre 2020): 421–31. http://dx.doi.org/10.1111/cgf.14156.

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Taylor, Sarah L., Idris A. Eckley e Matthew A. Nunes. "A Test of Stationarity for Textured Images". Technometrics 56, n. 3 (3 luglio 2014): 291–301. http://dx.doi.org/10.1080/00401706.2013.823890.

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Lizier, Mario A. S., David C. Martins, Alex J. Cuadros-Vargas, Roberto M. Cesar e Luis G. Nonato. "Generating segmented meshes from textured color images". Journal of Visual Communication and Image Representation 20, n. 3 (aprile 2009): 190–203. http://dx.doi.org/10.1016/j.jvcir.2009.01.002.

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Spann, M., e A. E. Grace. "Adaptive segmentation of noisy and textured images". Pattern Recognition 27, n. 12 (dicembre 1994): 1717–33. http://dx.doi.org/10.1016/0031-3203(94)90089-2.

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Hoffman, David K., Gemunu H. Gunaratne, D. S. Zhang e Donald J. Kouri. "A method to Fourier filter textured images". Chaos: An Interdisciplinary Journal of Nonlinear Science 10, n. 1 (marzo 2000): 240–47. http://dx.doi.org/10.1063/1.166490.

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Lekehali, Somia, e Abdelouahab Moussaoui. "Quantum Local Binary Pattern for Medical Edge Detection". Journal of Information Technology Research 12, n. 2 (aprile 2019): 36–52. http://dx.doi.org/10.4018/jitr.2019040103.

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Edge detection is one of the most important operations for extracting the different objects in medical images because it enables delimitation of the various structures present in the image. Most edge detection algorithms are based on the intensity variations in images. Edge detection is especially difficult when the images are textured, and it is essential to consider the texture in edge detection processes. In this article, the authors propose a new procedure to extract the texture from images, called the Quantum Local Binary Pattern (QuLBP). The authors introduce two applications that use QuLBP to detect edges in magnetic resonance images: a cellular automaton (CA) edge detector algorithm and a combination of the QuLBP and the Deriche-Canny algorithm for salt and pepper noise resistance. The proposed approach to extracting texture is designed for and applied to different gray scale image datasets with real and synthetic magnetic resonance imaging (MRI). The experiments demonstrate that the proposed approach produces good results in both applications, compared to classical algorithms.

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Kato, Zoltan, e Ting-Chuen Pong. "A Markov random field image segmentation model for color textured images". Image and Vision Computing 24, n. 10 (ottobre 2006): 1103–14. http://dx.doi.org/10.1016/j.imavis.2006.03.005.

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Liu, Guoying, Pengwei Li e Yun Zhang. "A Color Texture Image Segmentation Method Based on Fuzzy c-Means Clustering and Region-Level Markov Random Field Model". Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/240354.

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This paper presents a variation of the fuzzy local information c-means clustering (FLICM) algorithm that provides color texture image clustering. The proposed algorithm incorporates region-level spatial, spectral, and structural information in a novel fuzzy way. The new algorithm, called RFLICM, combines FLICM and region-level Markov random field model (RMRF) together to make use of large scale interactions between image patches instead of pixels. RFLICM can overcome the weakness of FLICM when dealing with textured images and at the same time enhances the clustering performance. The major characteristic of RFLICM is the use of a region-level fuzzy factor, aiming to guarantee texture homogeneity and preserve region boundaries. Experiments performed on synthetic and remote sensing images show that RFLICM is effective in providing accuracy to color texture images.

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Ganesan, L., C. Umarani, M. Kaliappan, S. Vimal, Seifedine Kadry e Yunyoung Nam. "Texture Image Analysis for Larger Lattice Structure using Orthogonal Polynomial framework". Information Technology and Control 51, n. 3 (23 settembre 2022): 531–44. http://dx.doi.org/10.5755/j01.itc.51.3.29322.

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An Orthogonal Polynomial Framework using 3 x 3 mathematical model has been proposed and attempted for the textureanalysis by L.Ganesan and P.Bhattacharyya during 1990. They proposed this frame work which was unified to address both edgeand texture detection. Subsequently, this work has been extended for different applications by them and by different authors overa period of time. Now the Orthogonal Polynomial Framework has been shown effective for larger grid size of (5 x 5) or (7 x 7) orhigher, to analyze textured surfaces. The image region (5 x 5) under consideration is evaluated to be textured or untextured usinga statistical approach. Once the image region is concluded to be textured, it is proposed to be described by a local descriptor,called pro5num, computed by a simple coding scheme on the individual pixels based on their computed significant variances. Thehistogram of all the pro5nums computed over the entire image, called pro5spectrum, is considered to be the global descriptor.The novelty of this scheme is that it can be used for discriminating the region under consideration is micro or macro texture,based on the range of values in the global descriptor. This method works fine for many standard texture images. The works usingthe proposed descriptors for many texture analysis problems with (5 x5) including higher grid size and applications are underprogress

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You, J., e H. A. Cohen. "Classification and segmentation of rotated and scaled textured images using texture “tuned” masks". Pattern Recognition 26, n. 2 (febbraio 1993): 245–58. http://dx.doi.org/10.1016/0031-3203(93)90033-s.

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Triwayuni, I. Gusti Ayu, I. Ketut Gede Darma Putra e I. Putu Agus Eka Pratama. "Content Based Image Retrieval Using Lacunarity and Color Moments Of Skin Diseases". Indonesian Journal of Electrical Engineering and Computer Science 9, n. 1 (1 gennaio 2018): 243. http://dx.doi.org/10.11591/ijeecs.v9.i1.pp243-248.

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<p><em>The research conducted contributed in the form of CBIR application which was developed using texture and color feature extraction in searching the contents information of an object of skin disease image. The textured feature is extracted using Lacunarity, while for color feature extraction using Color Moments as well as a combination of both methods. The results of color characteristic extraction test using Color Moments Method yielded images corresponding to 100% similarity percentages and experimentation of texture characteristic extraction using Lacunarity Method yielded images corresponding to a percentage of suitability of 25%, followed by a combined test of both methods and the normalization process produces images corresponding to a percentage of conformity of 60%.</em></p>

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Mao, Min, Kuang-Rong Hao e Yong-Sheng Ding. "Self-Similarity Based Corresponding-Point Extraction from Weakly Textured Stereo Pairs". Mathematical Problems in Engineering 2014 (2014): 1–20. http://dx.doi.org/10.1155/2014/568034.

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For the areas of low textured in image pairs, there is nearly no point that can be detected by traditional methods. The information in these areas will not be extracted by classical interest-point detectors. In this paper, a novel weakly textured point detection method is presented. The points with weakly textured characteristic are detected by the symmetry concept. The proposed approach considers the gray variability of the weakly textured local regions. The detection mechanism can be separated into three steps: region-similarity computation, candidate point searching, and refinement of weakly textured point set. The mechanism of radius scale selection and texture strength conception are used in the second step and the third step, respectively. The matching algorithm based on sparse representation (SRM) is used for matching the detected points in different images. The results obtained on image sets with different objects show high robustness of the method to background and intraclass variations as well as to different photometric and geometric transformations; the points detected by this method are also the complement of points detected by classical detectors from the literature. And we also verify the efficacy of SRM by comparing with classical algorithms under the occlusion and corruption situations for matching the weakly textured points. Experiments demonstrate the effectiveness of the proposed weakly textured point detection algorithm.

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STRZELECKI, MICHAŁ, JACEK KOWALSKI, HYONGSUK KIM e SOOHONG KO. "A NEW CNN OSCILLATOR MODEL FOR PARALLEL IMAGE SEGMENTATION". International Journal of Bifurcation and Chaos 18, n. 07 (luglio 2008): 1999–2015. http://dx.doi.org/10.1142/s0218127408021506.

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Segmentation of the textured images into disjoint homogeneous regions is a very important aspect of visual perception. The texture represents properties of visualized objects; it may provide information about their structure. One of the recently developed tools used for texture segmentation is a network of synchronized oscillators. A parallel network operation is based on a "temporary correlation" theory, which attempts to explain scene recognition as performed by the human brain. This theory states that the synchronized oscillations of neuron groups attract attention if it is focused on a coherent stimulus (image object). For more than one perceived stimulus, these synchronized patterns switch in time between different neuron groups, thus forming temporal maps coding several features of the analyzed scene. Consequently, to implement this theory, a new oscillator network was proposed for image segmentation. The segmentation is obtained due to local interactions among neighboring cells. Such a network was successfully used for segmentation of the wide range of different images, including textured and biomedical ones. The network is very suitable for a hardware realization owing to its parallel structure. The realization provides a much faster image segmentation when compared to computer simulation techniques. The paper presents a new mathematical oscillator model suitable to be implemented in a CNN network chip. The model was used to design and simulate a CMOS oscillator circuit, which enables parallel network operation. The proposed oscillator model was analyzed and discussed from the point of view of its computer simulations. Furthermore, it was demonstrated that the oscillator network which implements the presented model is able to perform segmentation of the sample textured images. Oscillator circuit and block diagram of the proposed network chip were also presented and discussed.

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Amorín, Harvey, Andréi L. Kholkin e Maria Elisabete V. Costa. "Texture – Property Relationships in Bi-Layered Ferroelectric Ceramics: A Case Study of SrBi₂Ta₂O₉". Materials Science Forum 514-516 (maggio 2006): 170–74. http://dx.doi.org/10.4028/www.scientific.net/msf.514-516.170.

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A quantitative model for the calculation of spontaneous polarization of BLSF ceramics as a function of the degree of texture is presented using a general formalism based on the texture analysis via an orientation distribution function. The March-Dollase equation was selected to fit the measured texture distribution because its fitting parameters can be related to experimentally measurable stereological values obtained from SEM images. The results are applied to the SrBi2Ta2O9 (SBT) system, which is a well-known member of the BLSF family. The textured SBT ceramics were fabricated by templated grain growth (TGG) and the microstructure and degree of texture were evaluated by SEM analysis, which allowed correlating the texture development to the sintering parameters. Enhanced ferroelectric properties were measured perpendicularly to the uniaxial pressing direction of the ceramics, revealing the influence of the grains orientation, anisotropy and volume fraction of textured material on the ferroelectric properties. Finally, the predicted values for the spontaneous polarization as a function of the degree of texture were compared with those measured from the hysteresis loops.

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Bennett, J., e A. Khotanzad. "Modeling textured images using generalized long correlation models". IEEE Transactions on Pattern Analysis and Machine Intelligence 20, n. 12 (1998): 1365–70. http://dx.doi.org/10.1109/34.735810.

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Puente Leo´n, Fernando. "Suppression of inhomogeneities in images of textured surfaces". Optical Engineering 36, n. 1 (1 gennaio 1997): 85. http://dx.doi.org/10.1117/1.601602.

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