Haralick Texture

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Image texture is a quantification of the spatial variation of grey tone values. Haralick et al. (1973) suggested the use of grey level co-occurrence matrices (GLCM). This method is based on the joint probability distributions of pairs of pixels. GLCM show how often each gray level occurs at a pixel located at a fixed geometric position relative to each other pixel, as a function of the gray level (Srinivasan and Shobha 2008). An essential component is the definition of eight nearest-neighbor resolution cells (Fig.) that define different matrices for different angles (0°,45°,90°,135°) and distances between the horizontal neighboring pixels.

3x3 window definition and spatial relationship for calculating Haralick texture measures. Pixel 1 and 5 are 0° (horizontal) nearest neighbors to the center pixel * ; pixel 2 and 6 are 135° nearest neighbors; pixels 3 and 7 are 90° nearest neighbors, pixel 4 and 8 are 45° nearest neighbors to the center pixel * (Haralick et al. 1973)
  • In the search engine of the Processing Toolbox, type texture and select HaralickTextureExtraction under Feature Extraction of OTB.
  • Under the Parameters tab, select a single band or a multiband file as input layer.
  • Select a band number in case of a multiband file under Selected Channel
  • Select the size of the neighborhood in x and y direction.
  • Specify the range of the grey levels for the specific input band in the Image minimum and Image maximum field. Check [Raster metadata] for correct values!
  • Select as number of bins for the histogram: 32.
  • Select the Texture Set: Simple

Otb haralick.png



  • The result file contains the following texture measures:
  1. Energy
  2. Entropy
  3. Correlation
  4. Inverse Difference Moment
  5. Inertia
  6. Cluster Shade
  7. Cluster Prominence
  8. Haralick Correlation
Figure A: Input image: Sentinel-2 band B2, (University Göttingen Campus North)
Figure B: Output image: Haralick textures (RGB= Haralick Correlation, Energy, Entropy)
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