Results 281 to 290 of about 93,638 (313)

A comprehensive approach for texture classification

10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010), 2010
Classification of textures based on wavelet pattern analysis is one of the most effective methods in texture classification. However using all frequency sub-bands in decomposition for classification may increase time complexity of classification algorithms.
P. A. Reddy, P. S. R. C. Murty, Edara Srinivasa Reddy 0001   +2 more
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Efficient Classification of Seismic Textures

2018 International Joint Conference on Neural Networks (IJCNN), 2018
One of the most critical activities for the oil and gas industry is the discovery of new possibles reserves. Geoscientists must rely on indirect measures of the subsurface to scrutinize huge areas looking for leads of hydrocarbon reservoirs. Usually, to study the Earth’s crust, geoscientists examine seismic images.
Daniel Salles Chevitarese, Daniela Szwarcman, Emilio Vital Brazil, Bianca Zadrozny   +3 more
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An adaptive model for texture classification

Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2002
This paper presents an adaptive texture model for texture classification. In this model, a texture is considered containing both structural and stochastic components. These two components are indeterministic and deterministic parts as in the Wold texture model that are represented by Gaussian Markov random field (GMRF) model and multichannel filtering ...
Yong Huang, Kap Luk Chan, ZhongYang Huang   +2 more
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A Comparison on Textured Motion Classification

2006
Textured motion – generally known as dynamic or temporal texture – analysis, classification, synthesis, segmentation and recognition is popular research areas in several fields such as computer vision, robotics, animation, multimedia databases etc.
Kaan Öztekin, Gozde Bozdagi Akar
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Texture classification using fuzzy uncertainty texture spectrum

Neurocomputing, 1998
Abstract A new method using fuzzy uncertainty, which measures the uncertainty of the uniform surface in an image, is proposed for texture analysis. A grey-scale image can be transformed into a fuzzy image by the uncertainty definition. The distribution of the membership in a measured fuzzy image, denoted by the fuzzy uncertainty texture spectrum ...
Yih-Gong Lee, Jia-Hong Lee, Yuang-Cheh Hsueh   +2 more
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A Novel Texture Sensor for Fabric Texture Measurement and Classification

IEEE Transactions on Instrumentation and Measurement, 2014
Surface texture is one of the important cues for human beings to identify different fabrics. This paper presents a novel design of a surface texture sensor by imitating human active texture perception by touch. A thin polyvinylidene fluoride (PVDF) film is used as the sensitive element to fabricate a high-accuracy, high-speed-response fabric surface ...
Aiguo Song, Yezhen Han, Haihua Hu, Jianqing Li 0006   +3 more
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Relational Features for Texture Classification

2011
Texture features play an important role in facilitating various applications, for instance, image retrieval and object recognition. In this work, we investigate the relational features as a texture descriptor in classifying materials and visual textures from their appearance.
Wan Nural Jawahir Hj Wan Yussof, Hans Burkhardt   +1 more
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Distributed learning of texture classification

1990
A large number of statistical measures have been postulated for the description and discrimination of textures. While most are useful in some situations, none are totally effective in all of them. An alternative approach is to learn which measures are best for particular circumstances.
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Dictionary Learning in Texture Classification

2011
Texture analysis is used in numerous applications in various fields. There have been many different approaches/techniques in the literature for texture analysis among which the texton-based approach that computes the primitive elements representing textures using k-means algorithm has shown great success. Recently, dictionary learning and sparse coding
Mehrdad J. Gangeh, Ali Ghodsi 0001, Mohamed S. Kamel   +2 more
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Review of Texture Descriptors for Texture Classification

2017
Texture classification is a process of distinguishing or classifying different textures into separate classes. Finding an efficient texture descriptor is a vital step for performing accurate texture classification. The research area of texture classification is widely investigated in several computer vision and pattern recognition problems.
Philomina Simon, V. Uma
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