Results 141 to 150 of about 429,650 (191)

Texture feature extraction

Pattern Recognition Letters, 1987
Abstract We present a new approach to texture feature extraction from a cooccurrence matrix. Computationally, the method is much faster than traditional uses of cooccurrence matrices. Using Brodatz's textures, the proposed features are evaluated and compared with those suggested by Conners et al. (1984).
Dong-Chen He, Li Wang, Jean Guibert
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Texture Classification from Random Features

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012
Inspired by theories of sparse representation and compressed sensing, this paper presents a simple, novel, yet very powerful approach for texture classification based on random projection, suitable for large texture database applications. At the feature extraction stage, a small set of random features is extracted from local image patches.
Li, Liu, Paul W, Fieguth
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Texture analysis: Algorithm for texture features computation

2012 IV International Conference "Problems of Cybernetics and Informatics" (PCI), 2012
Textures are one of the most important features in computer vision for many applications. Texture feature extraction has been an active topic for years. There are a lot of feature extraction methods for texture analysis. In this paper the features were constructed using novel algorithm.
Marina Lukashevich, Rauf Sadykhov
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Texture classification using color local texture features

2013 International Conference on Signal Processing , Image Processing & Pattern Recognition, 2013
This Paper proposes a new approach to extract the features of a color texture image for the purpose of texture classification. Four feature sets are involved. Dominant Neighbourhood Structure (DNS) is the new feature set that has been used for color texture image classification.
S. Arivazhagan, R. Benitta
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Structural Texture Features

2019
Structural methods depict texture through well-defined primitives and a structure of those primitives’ spatial relationships.
Jyotismita Chaki, Nilanjan Dey
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Statistical Texture Features

2019
Statistical methods calculate distinct texture characteristics and are appropriate if the size of the texture is similar to the size of the pixels.
Jyotismita Chaki, Nilanjan Dey
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Texture Features and Image Texture Models

2019
Image texture is an important phenomenon in many applications of pattern recognition and computer vision. Hence, several models for deriving texture properties have been proposed and developed. Although there is no formal definition of image texture in the literature, image texture is usually considered the spatial arrangement of grayscale pixels in a ...
Chih-Cheng Hung, Enmin Song, Yihua Lan
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Texture Image Classification Using Perceptual Texture Features and Gabor Wavelet Features

2009 Asia-Pacific Conference on Information Processing, 2009
Texture is a key component for human visual perception and plays an important role in image-related applications. This paper combines perceptual texture features and Gabor wavelet features for texture image classification. Three new texture features which are proved to be in accordance with human visual perception are introduced. These features include
Muwei Jian, Lei Liu, Feng Guo
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Construction of texture features

2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis, 2009
One well-known and effective method used for computationally efficient texture classification is the use of statistical information on 3×3 pixel blocks such as local binary patterns (LBP). However, there has been negligible research on sizes of pixel blocks beyond 3×3 while using the histogram approach. Specifically, larger or non-square features might
A. Oerlemans, null Qi Zhang, M.S. Lew
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Feature-preserving procedural texture

The Visual Computer, 2017
This paper presents how to synthesize a texture in a procedural way that preserves the features of the input exemplar. The exemplar is analyzed in both spatial and frequency domains to be decomposed into feature and non-feature parts. Then, the non-feature parts are reproduced as a procedural noise, whereas the features are independently synthesized ...
HyeongYeop Kang, Junghyun Han
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