The texture images are grayscale and taken under controlled lighting conditions. It was published in 1966 by Dover Publications.The texture images are grayscale and taken under controlled lighting conditions. Download dataset Download code Evaluation Citation f 0 1 78.3 77.7 74.7 75.6 78.2 80.9 76.0 73.8 80.0 81.4 77.7 f 1 76.4 76.1 74.2 75.2 78.7 78.5 75.8 73.0 77.3 80.5 76.6 f 1 jj f 1 95.0 87.9 77.0 63.6 65.7 71.1 64.2 75.5 92.0 96.4 78.8 f 1 jj f 1 jj f 1 95.0 87.7 76.2 63.8 65.5 70.2 65.0 73.9 92.2 96.4 78.6 PSU Near-Regular Texture Database : A collection of Near-Regular Textures. Each texture is accompanied by a brief description of the contents and the conditions under which it was taken, and a unique identifier. The Describable Textures Dataset (DTD) is an evolving collection of textural images in the wild, annotated with a series of human-centric attributes, inspired by the perceptual properties of textures. Texture Dataset Texture dataset without rotated patches as .zip or .7z files. Textures: A Photographic Album for Artists and Designers is a compendium of 112 texture photographs by Phil Brodatz. USPTex Dataset : 2292 samples of 191 texture classes (12 samples per class). Textures: A Photographic Album for Artists and Designers is a compendium of 112 texture photographs by Phil Brodatz. Brodatz Album Description (include details on usage, files and paper references) The Brodatz dataset consists of 112 textures in grayscale images of various texture types. Dynamic Texture Database : a diverse collection of high-quality dynamic texture videos. It is composed of 112 grayscale images representing a large variety of natural grayscale textures. Various algorithms exploit the Brodatz texture database for evaluations, though in most of the cases, the entire database is not employed. (~0.9 GB) Texture dataset with rotated patches as .zip or .7z files. texture. It is composed of 112 grayscale images representing a large variety of natural grayscale textures. For example, 23 distinct natural textures are selected from the Brodatz album in (Laine and Fan, 1993). Texture from this album can be digitized into di erent gray-levelintervalsresultingindi erentbackgroundintensities.In It was published in 1966 by Dover Publications. Each texture is accompanied by a brief description of the contents and the conditions under which it was taken, and a unique identifier. This new dataset complements the existing benchmarks (e.g. The detailed information on image dataset is given in Table A 1.1. Brodatz Texture Dataset : 112 texture images for synthesis and recognition. The Brodatz texture database is based on image rotated textures. The image data for texture classification contains 32 textures from the Brodatz album. is album provides a very useful natural texture database, which has been widely used to evaluate texture discrimination methods [ ]. We also introduced a new texture dataset, which contains rotated texture images from Brodatz’s Album. Feature extraction and machine learning based classification of brodatz's texture using keras and svm - saunair/Brodatz-texture-classification Dataset: Brodatz (13 classes, 16 samples class) Texture descriptor Rotation angle 00 10 20 30 40 50 60 70 80 90 Avg. The standard Brodatz grayscale texture album has been widely used as a validation dataset [16, 17]. This data is made available to the computer vision community for research purposes. Different papers use various number of image sets from this dataset. A good example of this type of texture is the texture images of the Brodatz album. (~10.7 GB) A small subset of the dataset including 6 classes with 40 samples each can be downloaded here as a .zip or .7z file. Brodatz, CUReT, PSU Near-regular Texture Dataset, etc. We used two image datasets to validate the proposed descriptor: the Kylberg Sintorn Rotation Dataset and the Brodatz Texture Rotation Dataset.
2020 brodatz texture dataset