Results 241 to 250 of about 1,823,626 (291)

Statistical geometrical features for texture classification [PDF]

Pattern Recognition, 1995
Abstract This paper proposes a novel set of 16 features based on the statistics of geometrical attributes of connected regions in a sequence of binary images obtained from a texture image. Systematic comparison using all the Brodatz textures shows that the new set achieves a higher correct classification rate than the well-known Statistical Gray ...
Yan Qiu Chen, Mark S. Nixon, David W. Thomas   +2 more
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Scale Sensitivity of Textural Features

2017
Prevailing surface material recognition methods are based on textural features but most of these features are very sensitive to scale variations and the recognition accuracy significantly declines with scale incompatibility between visual material measurements used for learning and unknown materials to be recognized.
Michal Haindl, Pavel Vácha
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Jordan features for texture segmentation

Proceedings of Third International Conference on Electronics, Circuits, and Systems, 2002
This paper deals with the application to texture segmentation of two concepts, namely the Jordan Decomposition Theorem, which says that any bounded variation function can be expressed as the difference of two non-decreasing functions, and the Peano-scan, which is a 1D traversal of square domains.
Dinu Coltuc, Jean-Marie Becker, Vasile Buzuloiu   +2 more
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Decorrelation Methods of Texture Feature Extraction

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1980
This paper presents the development and evaluation of a visual texture feature extraction method based on a stochastic field model of texture. Results of recent visual texture discrimination experiments are reviewed in order to establish necessary and sufficient conditions for texture features that are in agreement with human discrimination.
Olivier D. Faugeras, William K. Pratt
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Discriminative features for texture description

Pattern Recognition, 2012
In this paper, a feature extraction method is developed for texture description. To obtain discriminative patterns, we present a learning framework which is formulated into a three-layered model. It can estimate the optimal pattern subset of interest by simultaneously considering the robustness, discriminative power and representation capability of ...
Zhao Guoying, Pietikäinen Matti, Guo Yimo   +2 more
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A Method of the Extraction of Texture Feature

2008
In order to understand the emotional information of the color image, research focus has been shifted from designing sophisticated low-level feature extraction algorithms to reducing the `semantic gap' between the visual features and the richness of human perception. In this paper, we firstly get the ROI using the Eye tracker and divide every image into
Haifang Li 0001, Lihuan Men, Junjie Chen 0001   +2 more
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Texture features and learning similarity

Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1996
This paper addresses two important issues related to texture pattern retrieval: feature extraction and similarity search. A Gabor feature representation for textured images is proposed, and its performance in pattern retrieval is evaluated on a large texture image database. These features compare favorably with other existing texture representations. A
Wei-Ying Ma, B. S. Manjunath
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Fractal feature and texture analysis

Systems and Computers in Japan, 1988
AbstractAlthough fractal dimension is popular in computer graphics, it is not yet utilized adequately in image analysis. Thus, this paper presents an example of the application of fractal dimension to image analysis. First, the conventional fractal concept is described and then the possibilities of its application to image processing are discussed ...
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Feature-Based Texture Synthesis

2005
We introduce a new method for texture synthesis on regular and irregular example textures. In this paper, an enhanced patch-based algorithm is proposed to select patches with the best structural similarity and to avoid discontinuity at the boundary of adjacent patches.
Tong-Yee Lee, Chung-Ren Yan
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Texture discrimination based on an optimal utilization of texture features

Pattern Recognition, 1988
Abstract We present a new approach to texture discrimination based on an algorithm which automatically selects the texture features best suited to a particular classification problem. Promising results are obtained when applying the method to the discrimination of 10 Brodatz's features.
Dong-Chen He, Li Wang 0002, Jean Guibert
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