Results 1 to 10 of about 75,620 (164)
Impact of Exposure and Illumination on Texture Classification Based on Raw Spectral Filter Array Images [PDF]
Sensors, 2023 Spectral Filter Array cameras provide a fast and portable solution for spectral imaging. Texture classification from images captured with such a camera usually happens after a demosaicing process, which makes the classification performance rely on the ...
Omar Elezabi +2 more
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Compact Hybrid Multi-Color Space Descriptor Using Clustering-Based Feature Selection for Texture Classification [PDF]
Journal of Imaging, 2022 Color texture classification aims to recognize patterns by the analysis of their colors and their textures. This process requires using descriptors to represent and discriminate the different texture classes.
Mohamed Alimoussa +4 more
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Combination of LBP Bin and Histogram Selections for Color Texture Classification [PDF]
Journal of Imaging, 2020 LBP (Local Binary Pattern) is a very popular texture descriptor largely used in computer vision. In most applications, LBP histograms are exploited as texture features leading to a high dimensional feature space, especially for color texture ...
Alice Porebski +3 more
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Cirrhosis classification based on texture classification of random features. [PDF]
Comput Math Methods Med, 2014 Accurate staging of hepatic cirrhosis is important in investigating the cause and slowing down the effects of cirrhosis. Computer-aided diagnosis (CAD) can provide doctors with an alternative second opinion and assist them to make a specific treatment with accurate cirrhosis stage.
Liu H +5 more
europepmc +5 more sources
A Nested Texture Inspired Novel Image Pattern Based Optical Camera Communication
IEEE Access, 2022 Pattern recognition is a vital component of display-based optical camera communication. However, as the distance between the transmitter LED panel and the receiver camera increases, the visibility of the pattern reduces.
Sanket Salvi, V. Geetha
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Effective Defect Detection Method Based on Bilinear Texture Features for LGPs
IEEE Access, 2021 Automatic defect detection of light guide plates (LGPs) is an important task in the manufacture of liquid crystal displays. During thermo-printing, defects of tag lines on LGPs may occur easily, and these defects are of two categories: bubbles and ...
Libin Hong +3 more
doaj +1 more source
Texture Classification with Ants [PDF]
2006 International Conference on Image Processing, 2006 In this paper, we present a novel texture classification algorithm inspired by the self-assembling behavior of real ants when building live structures with their bodies. The proposed algorithm employs dyadic Gabor filter banks for extracting discriminant features from images containing multiple textures not known to the algorithm.
Arshad Hussain +2 more
openaire +1 more source
Quaternionic wavelets for texture classification [PDF]
2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010 This article proposes a study of the recent quaternionic wavelet transform (QWT) from a practical point of view through a digital image analysis application. Based on a theoretic 2D generalization of the analytic signal leading to a strong 2D signal modeling, this representation uses actual 2D analytic wavelets and yields subbands having a shift ...
Soulard, Raphaël, Carré, Philippe
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An integrated descriptor for texture classification [PDF]
2016 23rd International Conference on Pattern Recognition (ICPR), 2016 Regarding texture features, Local-based methods such as Local Binary Pattern (LBP) and its variants are computationally efficient high-performing but sensitive to noise, and suffering global structure information loss. By contrast, filter-based counterparts, the Scattering Transform for instance, are tolerant to noise and translation but often lack of ...
Vu-Lam Nguyen +3 more
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Classification of natural textures in echolocation [PDF]
Proceedings of the National Academy of Sciences, 2004 Through echolocation, a bat can perceive not only the position of an object in the dark; it can also recognize its 3D structure. A tree, however, is a very complex object; it has thousands of reflective surfaces that result in a chaotic acoustic image of the tree. Technically, the acoustic image of an object is its impulse response (IR), i.
Jan-Eric, Grunwald +2 more
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