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"Texture"
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\"Compares and contrasts common rough and smooth objects, both in nature and man-made. Includes comprehension activity\"--Provided by publisher.
Book
T1K+: A Database for Benchmarking Color Texture Classification and Retrieval Methods
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.
Journal Article
Multi-order texture features for palmprint recognition
Palmprint attracts increasing attention thanks to its several advantages. 1st-order textures have been widely used for palmprint recognition; unfortunately, high-order textures, although they are also discriminative, were ignored in the existing works. 2nd-order textures are first employed for palmprint recognition in this paper. 1st-order textures are convolved with the filters to extract 2nd-order textures that can refine the texture information and improve the contrast of the feature map. Then 2nd-order textures are used to generate 2nd-order Texture Co-occurrence Code (2TCC). The sufficient experiments demonstrate that 2TCC yields satisfactory accuracy performance on four public databases, including contact, contactless and multi-spectral acquisition types. Moreover, in order to further improve the discrimination and robustness of 2TCC, we propose Multiple-order Texture Co-occurrence Code (MTCC), in which 1st-order Texture Co-occurrence Code (1TCC) and 2TCC are fused at score level. 1TCC is good at describing minor wrinkles; while 2TCC does well in describing principal textures. Thus the combination of both can describe the palmprint features more comprehensively. MTCC achieves remarkable accuracy performance when compared with the state-of-the-art methods on all public databases.
Journal Article
Study of Pavement Micro- and Macro-Texture Evolution Due to Traffic Polishing Using 3D Areal Parameters
Pavement micro- and macro-texture have significant effects on roadway friction and driving safety. The influence of traffic polish on pavement texture has been investigated in many laboratory studies. This paper conducts field evaluation of pavement micro- and macro-texture under actual traffic polishing using three-dimensional (3D) areal parameters. A portable high-resolution 3D laser scanner measured pavement texture from a field site in 2018, 2019, and 2020. Then, the 3D texture data was decomposed to micro- and macro-texture using Fourier transform and Butterworth filter methods. Twenty 3D areal parameters from five categories, including height, spatial, hybrid, function, and feature parameters, were calculated to characterize pavement micro- and macro-texture. The results demonstrate that the 3D areal parameters provide an alternative to comprehensively characterize the evolution of pavement texture under traffic polish from different aspects.
Journal Article
Watercolor textures for artists : explore simple techniques to create amazing works of art
\"From popular artist, author, and online art instructor Ana Victoria Calderón, Watercolor Textures for Artists teaches how to paint simple watercolor textures and use them to create beautiful artworks that help cultivate relaxation and mindfulness\"-- Provided by publisher.
BOOK
BIPOLAR FUZZY CENTRED TEXTURE DI TOPOLOGICAL SPACES
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.
Journal Article
Deep Filter Banks for Texture Recognition, Description, and Segmentation
Visual textures have played a key role in image understanding because they convey important semantics of images, and because texture representations that pool local image descriptors in an orderless manner have had a tremendous impact in diverse applications. In this paper we make several contributions to texture understanding. First, instead of focusing on texture instance and material category recognition, we propose a human-interpretable vocabulary of texture attributes to describe common texture patterns, complemented by a new
describable texture dataset
for benchmarking. Second, we look at the problem of recognizing materials and texture attributes in realistic imaging conditions, including when textures appear in clutter, developing corresponding benchmarks on top of the recently proposed OpenSurfaces dataset. Third, we revisit classic texture represenations, including bag-of-visual-words and the Fisher vectors, in the context of deep learning and show that these have excellent efficiency and generalization properties if the convolutional layers of a deep model are used as filter banks. We obtain in this manner state-of-the-art performance in numerous datasets well beyond textures, an efficient method to apply deep features to image regions, as well as benefit in transferring features from one domain to another.
Journal Article