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Journal articles on the topic 'Textured images'

Author: Grafiati

Published: 1 June 2024

Last updated: 31 July 2025

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1

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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2

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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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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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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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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6

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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7

Beschastnov, Nikolay P., Irina V. Rybaulina, and Evdokia N. Dergileva. "FACTURE, TEXTURE AND TEHNO-ORNAMENT IN MODERN DESIGN: FUNCTION AND ARTISTIC MEANING." Technologies & Quality 51, no. 1 (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 mod

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8

Barburiceanu, Stefania, Romulus Terebes, and Serban Meza. "3D Texture Feature Extraction and Classification Using GLCM and LBP-Based Descriptors." Applied Sciences 11, no. 5 (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 informat

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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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10

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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11

Lehmann, F. "Turbo Segmentation of Textured Images." IEEE Transactions on Pattern Analysis and Machine Intelligence 33, no. 1 (2011): 16–29. http://dx.doi.org/10.1109/tpami.2010.58.

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12

Park, Jaehyun, and Ludwik Kurz. "Unsupervised segmentation of textured images." Information Sciences 92, no. 1-4 (1996): 255–76. http://dx.doi.org/10.1016/0020-0255(96)00047-3.

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13

Otazu, Xavier, and Maria Vanrell. "Perceptual Representation of Textured Images." Journal of Imaging Science and Technology 49, no. 3 (2005): 262–71. http://dx.doi.org/10.2352/j.imagingsci.technol.2005.49.3.art00007.

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14

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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15

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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16

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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17

Fu, Ying, Xiaohua Li, Lei Liang, Yi Zhang, and 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 propose

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18

Lai, Jiing-Yih, Tsung-Chien Wu, Watchama Phothong, Douglas Wang, Chao-Yaug Liao, and Ju-Yi Lee. "A High-Resolution Texture Mapping Technique for 3D Textured Model." Applied Sciences 8, no. 11 (2018): 2228. http://dx.doi.org/10.3390/app8112228.

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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 islan

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19

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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20

Park, Chang-Min, and Chang-Geun Kim. "Automatic Segmentation for Textured Object Images." International Journal of Multimedia and Ubiquitous Engineering 9, no. 9 (2016): 93–100. http://dx.doi.org/10.14257/ijmue.2016.11.9.10.

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21

Bouman, C., and B. Liu. "Multiple resolution segmentation of textured images." IEEE Transactions on Pattern Analysis and Machine Intelligence 13, no. 2 (1991): 99–113. http://dx.doi.org/10.1109/34.67641.

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22

Jain, Palak, and 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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23

Li, Fang, Chaomin Shen, Chunli Shen, and Guixu Zhang. "Variational denoising of partly textured images." Journal of Visual Communication and Image Representation 20, no. 4 (2009): 293–300. http://dx.doi.org/10.1016/j.jvcir.2009.01.003.

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24

Wu, Hai-Shan, Joseph Barba, and Joan Gil. "Morphological Segmentation of Textured Cell Images." Journal of Imaging Science and Technology 40, no. 3 (1996): 265–70. http://dx.doi.org/10.2352/j.imagingsci.technol.1996.40.3.art00013.

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25

Salem, Amr, Hussien Hegab, and Hossam A. Kishawy. "Experimental Investigation of the Derivative Cutting When Machining AISI 1045 with Micro-Textured Cutting Tools." Metals 13, no. 9 (2023): 1587. http://dx.doi.org/10.3390/met13091587.

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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 der

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26

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

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27

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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28

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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29

sandhu, Tajman. "Domain Specific CBIR for Highly Textured Images." Computer Science & Engineering: An International Journal 3, no. 2 (2013): 33–39. http://dx.doi.org/10.5121/cseij.2013.3203.

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30

Wu, H. S., J. Barba, and J. Gil. "Region growing segmentation of textured cell images." Electronics Letters 32, no. 12 (1996): 1084. http://dx.doi.org/10.1049/el:19960738.

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31

Zhang, Zhe, Panpan Xu, Jian Chang, Wencheng Wang, Chong Zhao, and Jian Jun Zhang. "Generating High‐quality Superpixels in Textured Images." Computer Graphics Forum 39, no. 7 (2020): 421–31. http://dx.doi.org/10.1111/cgf.14156.

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32

Taylor, Sarah L., Idris A. Eckley, and Matthew A. Nunes. "A Test of Stationarity for Textured Images." Technometrics 56, no. 3 (2014): 291–301. http://dx.doi.org/10.1080/00401706.2013.823890.

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33

Lizier, Mario A. S., David C. Martins, Alex J. Cuadros-Vargas, Roberto M. Cesar, and Luis G. Nonato. "Generating segmented meshes from textured color images." Journal of Visual Communication and Image Representation 20, no. 3 (2009): 190–203. http://dx.doi.org/10.1016/j.jvcir.2009.01.002.

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34

Spann, M., and A. E. Grace. "Adaptive segmentation of noisy and textured images." Pattern Recognition 27, no. 12 (1994): 1717–33. http://dx.doi.org/10.1016/0031-3203(94)90089-2.

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35

Hoffman, David K., Gemunu H. Gunaratne, D. S. Zhang, and Donald J. Kouri. "A method to Fourier filter textured images." Chaos: An Interdisciplinary Journal of Nonlinear Science 10, no. 1 (2000): 240–47. http://dx.doi.org/10.1063/1.166490.

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36

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

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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

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37

I, Gusti Ayu Triwayuni, Ketut Gede Darma Putra I, and Putu Agus Eka Pratama I. "Content Based Image Retrieval Using Lacunarity and Color Moments of Skin Diseases." Indonesian Journal of Electrical Engineering and Computer 9, no. 1 (2018): 243–48. https://doi.org/10.11591/ijeecs.v9.i1.pp243-248.

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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 correspondin

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38

You, J., and H. A. Cohen. "Classification and segmentation of rotated and scaled textured images using texture “tuned” masks." Pattern Recognition 26, no. 2 (1993): 245–58. http://dx.doi.org/10.1016/0031-3203(93)90033-s.

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Berezina, S. I., Yu O. Gordienko, and O. I. Solonets. "ANALYSIS OF WAYS OF SOLVING THE SEGMENTATION PROBLEM FOR HIGHLY TEXTURED OBJECTS." Проблеми створення, випробування, застосування та експлуатації складних інформаційних систем, no. 17 (December 30, 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

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Lekehali, Somia, and Abdelouahab Moussaoui. "Quantum Local Binary Pattern for Medical Edge Detection." Journal of Information Technology Research 12, no. 2 (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 Qu

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Liu, Guoying, Pengwei Li, and 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 char

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Yue, Yaoshun, Wenpeng Sang, Kaiwei Zhai, and Maohai Lin. "Enhanced Scratch Detection for Textured Materials Based on Optimized Photometric Stereo Vision and Fast Fourier Transform–Gabor Filtering." Applied Sciences 14, no. 17 (2024): 7812. http://dx.doi.org/10.3390/app14177812.

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In the process of scratch defect detection in textured materials, there are often problems of low efficiency in traditional manual detection, large errors in machine vision, and difficulty in distinguishing defective scratches from the background texture. In order to solve these problems, we developed an enhanced scratch defect detection system for textured materials based on optimized photometric stereo vision and FFT-Gabor filtering. We designed and optimized a novel hemispherical image acquisition device that allows for selective lighting angles. This device integrates images captured under

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43

Slavov, Stoyan Dimitrov, Lyubomir Si Bao Van, Marek Vozár, Peter Gogola, and Diyan Minkov Dimitrov. "Research on AI-Driven Classification Possibilities of Ball-Burnished Regular Relief Patterns Using Mixed Symmetrical 2D Image Datasets Derived from 3D-Scanned Topography and Photo Camera." Symmetry 17, no. 7 (2025): 1131. https://doi.org/10.3390/sym17071131.

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The present research is related to the application of artificial intelligence (AI) approaches for classifying surface textures, specifically regular reliefs patterns formed by ball burnishing operations. A two-stage methodology is employed, starting with the creation of regular reliefs (RRs) on test parts by ball burnishing, followed by 3D topography scanning with Alicona device and data preprocessing with Gwyddion, and Blender software, where the acquired 3D topographies are converted into a set of 2D images, using various virtual camera movements and lighting to simulate the symmetrical fluc

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44

Triwayuni, I. Gusti Ayu, I. Ketut Gede Darma Putra, and 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, no. 1 (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

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45

Mao, Min, Kuang-Rong Hao, and 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 weakl

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Kim, Jae-In, Chang-Uk Hyun, Hyangsun Han, and Hyun-cheol Kim. "Evaluation of Matching Costs for High-Quality Sea-Ice Surface Reconstruction from Aerial Images." Remote Sensing 11, no. 9 (2019): 1055. http://dx.doi.org/10.3390/rs11091055.

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Abstract:

Satellite remote sensing can be used effectively with a wide coverage and repeatability in large-scale Arctic sea-ice analysis. To produce reliable sea-ice information, satellite remote-sensing methods should be established and validated using accurate field data, but obtaining field data on Arctic sea-ice is very difficult due to limited accessibility. In this situation, digital surface models derived from aerial images can be a good alternative to topographical field data. However, to achieve this, we should discuss an additional issue, i.e., that low-textured surfaces on sea-ice can reduce

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Bennett, J., and A. Khotanzad. "Modeling textured images using generalized long correlation models." IEEE Transactions on Pattern Analysis and Machine Intelligence 20, no. 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, no. 1 (1997): 85. http://dx.doi.org/10.1117/1.601602.

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Bandera, Antonio, Cristina Urdiales, Fabián Arrebola, and Francisco Sandoval. "Scale-dependent hierarchical unsupervised segmentation of textured images." Pattern Recognition Letters 22, no. 2 (2001): 171–81. http://dx.doi.org/10.1016/s0167-8655(00)00103-3.

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Gimel'Farb, Georgy L., and Anil K. Jain. "On retrieving textured images from an image database." Pattern Recognition 29, no. 9 (1996): 1461–83. http://dx.doi.org/10.1016/0031-3203(96)00011-8.

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