In this paper we present T1K+, a very large, heterogeneous database of high-quality texture images acquired under variable conditions. T1K+ contains 1129 classes of textures ranging from natural ...subjects to food, textile samples, construction materials, etc. T1K+ allows the design of experiments especially aimed at understanding the specific issues related to texture classification and retrieval. To help the exploration of the database, all the 1129 classes are hierarchically organized in 5 thematic categories and 266 sub-categories. To complete our study, we present an evaluation of hand-crafted and learned visual descriptors in supervised texture classification tasks.
•Principles of texture analysis and modeling methods and their applications are reviewed.•Different methods of texture profile analysis, indices and modeling approaches are covered.•Advantages and ...limitations of different texture analysis approaches are discussed.
Texture analysis and modeling are important techniques in food and postharvest research and industrial practice. A wide range of methods have been used to evaluate instrumental results, which provide time-series data of product deformation, thereby allowing a wide range of texture attributes to be calculated from force–time or force–displacement data. Several indices of texture such as the firmness index, crunchiness index and texture index based on “vibration energy density” have been reported, but these are not widely used to quantify food texture. Some modeling and statistical approaches have been adopted to analyze food texture data, including chemical reaction kinetics and the Michaelis–Menton type decay function, mechanistic autocatalytic models based on logistic equation, and the finite element method. However, increasing demand for comprehensive approaches to texture profile analysis, generalized texture indices and fundamental texture models still remain challenges in the food research and industry.
Research in colour and texture has experienced major changes in the last few years. This book presents some recent advances in the field, specifically in the theory and applications of colour texture ...analysis. This volume also features benchmarks, comparative evaluations and reviews.
Solid texture synthesis from 2D exemplars Kopf, Johannes; Fu, Chi-Wing; Cohen-Or, Daniel ...
ACM transactions on graphics,
07/2007, Letnik:
26, Številka:
3
Journal Article
Recenzirano
Odprti dostop
We present a novel method for synthesizing solid textures from 2D texture exemplars. First, we extend 2D texture optimization techniques to synthesize 3D texture solids. Next, the non-parametric ...texture optimization approach is integrated with histogram matching, which forces the global statistics of the synthesized solid to match those of the exemplar. This improves the convergence of the synthesis process and enables using smaller neighborhoods. In addition to producing compelling texture mapped surfaces, our method also effectively models the material in the interior of solid objects. We also demonstrate that our method is well-suited for synthesizing textures with a large number of channels per texel.
•Evaluating statistical, transform, model, and structural-based texture features for DIR•Comparative analysis of the DIR results obtained from 26 texture features•Providing a computational time ...analysis of texture features used for DIR
Due to the rapid increase of different digitised documents, there has been significant attention dedicated to document image retrieval over the past two decades. Finding discriminative and effective features is a fundamental task for providing a fast and more accurate retrieval system. Texture features are generally fast to compute and are suitable for large volume data. Thus, in this study, the effectiveness of texture features widely used in the literature of content-based image retrieval is investigated on document images. Twenty-six different texture feature extraction methods from four main categories of texture features, statistical, transform, model, and structural-based approaches, are considered in this research work to compare their performance on the problem of document image retrieval. Three document image datasets, MTDB, ITESOFT, and CLEF_IP with various content and page layouts are used to evaluate the twenty-six texture-based features on document image retrieval systems. The retrieval results are computed in terms of precision, recall and F-score, and a comparative analysis of the results is also provided. Feature dimensions and time complexity of the texture-based feature methods are further compared. Finally, some conclusions are drawn and suggestions are made about future research directions.
Abstract
The bipolar fuzzy theory is a very effective tool for addressing real life problems in various field such as disease diagnosis, spatial information, image processing and engineering etc. The ...novel concepts of bipolar fuzzy centred system and bipolar fuzzy centred texture di topological spaces are introduced. Then we established the significance of bipolar fuzzy centred texture compactness, bipolar fuzzy centred texture nearly compactness and discussed some interesting characterizations on it. Finally, defined the idea of bipolar fuzzy centred texture nearly stable and bipolar fuzzy centred texture nearly co stable and its properties are also studied.
This paper is concerned with the representation and recognition of the observed dynamics (i.e., excluding purely spatial appearance cues) of spacetime texture based on a spatiotemporal orientation ...analysis. The term "spacetime texture" is taken to refer to patterns in visual spacetime, (x,y,t), that primarily are characterized by the aggregate dynamic properties of elements or local measurements accumulated over a region of spatiotemporal support, rather than in terms of the dynamics of individual constituents. Examples include image sequences of natural processes that exhibit stochastic dynamics (e.g., fire, water, and windblown vegetation) as well as images of simpler dynamics when analyzed in terms of aggregate region properties (e.g., uniform motion of elements in imagery, such as pedestrians and vehicular traffic). Spacetime texture representation and recognition is important as it provides an early means of capturing the structure of an ensuing image stream in a meaningful fashion. Toward such ends, a novel approach to spacetime texture representation and an associated recognition method are described based on distributions (histograms) of spacetime orientation structure. Empirical evaluation on both standard and original image data sets shows the promise of the approach, including significant improvement over alternative state-of-the-art approaches in recognizing the same pattern from different viewpoints.
With the coming era of cloud technology, cloud storage is an emerging technology to store massive digital images, which provides steganography a new fashion to embed secret information into massive ...images. Specifically, a resourceful steganographer could embed a set of secret information into multiple images adaptively, and share these images in cloud storage with the receiver, instead of traditional single image steganography. Nevertheless, it is still an open issue how to allocate embedding payload among a sequence of images for security performance enhancement. This article formulates adaptive payload distribution in multiple images steganography based on image texture features and provides the theoretical security analysis from the steganalyst's point of view. Two payload distribution strategies based on image texture complexity and distortion distribution are designed and discussed, respectively. The proposed strategies can be employed together with these state-of-the-art single image steganographic algorithms. The comparisons of the security performance against the modern universal pooled steganalysis are given. Furthermore, this article compares the per image detectability of these multiple images steganographic schemes against the modern single image steganalyzer. Extensive experimental results show that the proposed payload distribution strategies could obtain better security performance.
•Low carbon steel was annealed at 700 or 800 °C for 5–10 min. in an electric furnace.•Lower annealing temperatures (700 °C) showed bimodal ferrite grain distribution.•Steel annealed at 700 °C for ...5 min. exhibited detrimental cube texture, ND//〈001〉.•Increased annealing time and temperature led to strong γ-fiber, ND//〈111〉 .•Steel annealed at 800 °C for 10 min. showed the highest tensile elongation of 37 %.
This study investigated the effect of annealing temperature and time on the grain distribution and textural development of commercial-grade low-carbon steel that undergone cold rolling and subsequent electric-furnace annealing at either 700 or 800 °C for 5 and 10 min. Scanning electron microscopy and electron backscatter diffraction analyses of the annealed samples revealed equiaxed microstructures with cementite at the ferrite grain boundaries. The samples annealed at 700 °C for 5 and 10 min exhibited a bimodal grain distribution, while larger ferrite grains formed at 800 °C. The orientation distribution function texture of the sample annealed at 700 °C for 5 min exhibited both a γ-fiber ND//〈111〉 and a cube texture ND//〈001〉 . Raising the annealing temperature and time reduced the intensity of cube texture and strengthened the γ-fiber, increasing tensile elongation from 8 to 38 %.
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•A systematic literature survey on 3D texture analysis in biomedical imaging is proposed.•The taxonomy of 3D texture analysis is formally defined to accurately define the scope of the ...survey.•The application domains are reviewed based on imaging modality and organs.•The techniques are described, regrouped and categorized based on their type of model assumptions.•Future research directions are proposed based on the limitations of the available studies.
Three-dimensional computerized characterization of biomedical solid textures is key to large-scale and high-throughput screening of imaging data. Such data increasingly become available in the clinical and research environments with an ever increasing spatial resolution. In this text we exhaustively analyze the state-of-the-art in 3-D biomedical texture analysis to identify the specific needs of the application domains and extract promising trends in image processing algorithms. The geometrical properties of biomedical textures are studied both in their natural space and on digitized lattices. It is found that most of the tissue types have strong multi-scale directional properties, that are well captured by imaging protocols with high resolutions and spherical spatial transfer functions. The information modeled by the various image processing techniques is analyzed and visualized by displaying their 3-D texture primitives. We demonstrate that non-convolutional approaches are expected to provide best results when the size of structures are inferior to five voxels. For larger structures, it is shown that only multi-scale directional convolutional approaches that are non-separable allow for an unbiased modeling of 3-D biomedical textures. With the increase of high-resolution isotropic imaging protocols in clinical routine and research, these models are expected to best leverage the wealth of 3-D biomedical texture analysis in the future. Future research directions and opportunities are proposed to efficiently model personalized image-based phenotypes of normal biomedical tissue and its alterations. The integration of the clinical and genomic context is expected to better explain the intra class variation of healthy biomedical textures. Using texture synthesis, this provides the exciting opportunity to simulate and visualize texture atlases of normal ageing process and disease progression for enhanced treatment planning and clinical care management.
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