one well-known method of determining lacunarity for patterns extracted from digital images uses box counting, the same essential algorithm typically used for some types of fractal analysis. similar to looking at a slide through a microscope with changing levels of magnification, box counting algorithms look at a digital image from many levels of resolution to examine how certain features change with the size of the element used to inspect the image. basically, the arrangement of pixels is measured using traditionally square (i.e., box-shaped) elements from an arbitrary set of formula_3 sizes, conventionally denoted formula_4s. for each formula_4, the box is placed successively over the entire image, and each time it is laid down, the number of pixels that fall within the box is recorded. in standard box counting, the box for each formula_4 in formula_3 is placed as though it were part of a grid overlaid on the image so that the box does not overlap itself, but in sliding box algorithms the box is slid over the image so that it overlaps itself and the "sliding box lacunarity" or slac is calculated. figure 2 illustrates both types of box counting.