Object Classification (Actual Image Segmentation)

Deciding which class (or label) each object belongs to is simple a matter of comparing the results of the Dirichlet equation for each and every pixel in the image.

For each pixel in the image, the Dirichlet equation is implemented n times, once for each of the n user-provided labels. The results of each pixel for each label are then stored in n arrays and then a comparison must be made. Each pixel is cross checked across each of the arrays (i.e. pixel 2x3 will be compared with every other pixel at location 2x3 in the rest of the arrays). A new array will then be created which will contain the highest value of each pixel from all of the arrays (i.e. the highest of all the 2x3 pixels and the highest of all the 4x8 pixels, etc). This array will be the segmented image, or will be the mask of the segmented image.