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<title>Rapid Texture Identification</title>

Abstract

A method is presented for classifying each pixel of a textured image, and thus for segmenting the scene. The "texture energy" approach requires only a few convolutions with small (typically 5x5) integer coefficient masks, followed by a moving-window absolute average operation. Normalization by the local mean and standard deviation eliminates the need for histogram equalization. Rotation-invariance can also be achieved by using averages of the texture energy features. The convolution masks are separable, and can be implemented with 1-dimensional (vertical and horizontal) or multipass 3x3 convolutions. Special techniques permit rapid processing on general-purpose digital computers.

Industrial Vision Systems and Defect DetectionImage Processing and 3D ReconstructionImage Retrieval and Classification TechniquesComputer scienceNormalization (sociology)HistogramPixelArtificial intelligenceComputer visionStandard deviationTexture (cosmology)Energy (signal processing)Separable space
Citations
543
FWCI
2.10
field-weighted impact
References
0
Percentile
89%
vs. same field & year
Citations per year
Cited by
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