Skeletonizing Digital Images with Cellular Automata - Cellular Automata in Image Processing and Geometry - page 56

Fig. 3.8 The binarization of a real photograph and its skeleton

case, the skeletonization of the image with inverted colors is more meaningful .In
Fig. 3.8, we can see two black and white images of 789 1317 pixels. On the left,

the result of the binarization of a real photograph and its skeletonization on the right.
A last example is presented in Fig. 3.9. On the left, a fingerprint is shown and
on the right, its skeletonization. The basic problem with fingerprints is to determine
whether two fingerprints come from the same finger. There exist multiple algorithms
that do fingerprint matching in many different ways. Some methods involve match-
ing minutiae points between the two images, while others look for similarities in the

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Fig. 3.9 A fingerprint and its skeleton