In many cases, the objects or structures that need to be distinguished in images are not characterized by color or brightness values that are different from the surrounding background. Instead, the difference may be one of texture. Human vision recognizes features based on this property. In the illustrations in the Distinguishing Textures interactive tutorial, starting with an artificial texture and then in a light microscope image of cheese and an electron microscope image of liver tissue, there is no unique brightness difference in the original structures, but by calculating either the range or the variance of the pixel values in a neighborhood with radius = 2.5 pixels each distinct region is assigned a different brightness. Notice that the image histogram after processing has distinct peaks that correspond to the structures.

	Interactive Tutorial
Distinguishing Textures Discover how to convert spatial texture to brightness values.

Texture or structure in an image may also have directionality. This can be detected as a property and used to label regions by applying the same Sobel brightness gradient vector introduced above as an edge delineation tool. The magnitude of the vector was used to outline steps and edges. The orientation angle of the vector can be used to characterize local orientation. The angle from 0 to 180 or from 0 to 360 degrees is generally scaled to the 0..255 brightness range of the display, or shown as a color, as illustrated in the Distinguishing Directionality interactive tutorial. For the directions and cloth images this shows that the visually distinct regions of the image can be separated by the procedure. For the collagen image, the histogram is a quantitative measure of the preferred orientation of the fibers.

	Interactive Tutorial
Distinguishing Directionality Explore methods for converting spatial orientation to brightness values.

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