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Kompletny słownik sztucznej inteligencji

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kategorie
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podkategorie
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pojęcia
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Gray-Level Co-occurrence Matrix (GLCM)

A statistical matrix that describes the frequency of occurrence of pixel pairs with specific intensity values at a given direction and distance, used to extract second-order textural features.

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Haralick Texture Descriptors

A set of 14 statistical features calculated from the GLCM including contrast, homogeneity, energy, and correlation, used to quantify the textural properties of digital images.

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Gabor Transform

A spatial-frequency analysis method using Gaussian filters modulated by sinusoids to capture textural features at different scales and orientations.

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Local Binary Patterns (LBP)

A texture operator that encodes the micro-structural relationships between a central pixel and its neighbors into binary values, creating a robust histogram for texture classification.

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Fractal Analysis

A mathematical approach measuring the complexity and self-similarity of textures at different scales, often used to quantify the roughness of natural surfaces.

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Wavelets for Texture Analysis

A multi-resolution decomposition using wavelet functions to extract textural features at different spatial frequencies and orientations simultaneously.

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Texture Invariant Moments

Mathematical descriptors based on the statistical moments of the intensity histogram, invariant to geometric transformations for robust texture recognition.

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Spatial Autocorrelation

A statistical measure quantifying the correlation of pixel values at different spatial distances, characterizing the periodicity and regularity of textural patterns.

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Texture Markov Models

Probabilistic approach modeling the statistical dependency between neighboring pixels to characterize and synthesize textures based on local contextual relationships.

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2D Power Spectrum

Frequency representation obtained by Fourier transform revealing directional and periodic components of textures for their analysis and classification.

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Laws' Texture Energy

Set of 5x5 convolution masks to detect fundamental textural primitives like levels, edges, spots, and ripples in images.

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Texture Anisotropy

Measure of the directional dependency of textural features, quantifying how properties vary across different orientations in the image.

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Texture Entropy

Informational measure quantifying the degree of disorder or unpredictability in the pixel intensity distribution of a textured region.

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Convolutional Neural Networks for Texture

Deep learning architecture using automatically learnable filters to extract hierarchies of complex textural features from raw images.

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Texture Segmentation

Process of partitioning an image into homogeneous regions based on similarities in textural features rather than solely on intensity differences.

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Example-based Texture Synthesis

Technique generating new textures by sampling and recombining patches from a source texture while preserving local and global statistical characteristics.

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Histogram of Oriented Gradients (HOG)

Descriptor counting occurrences of gradient orientation in localized portions of an image, effective for capturing directional texture structures.

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3D Texture Analysis

Extension of texture analysis methods to the volumetric domain, considering three-dimensional relationships of voxels to characterize textured surfaces and volumes.

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