An Anisotropic Interaction Model for Simulating Fingerprints
For biometrics and forensic science, this model provides a more biologically plausible method for generating synthetic fingerprints, though it is an incremental improvement over the existing Kücken-Champod model.
The paper proposes a new anisotropic interaction model for fingerprint pattern formation that incorporates a tensor field representing epidermal stress, enabling the generation of complex, stationary patterns with rescaling properties. The model is validated analytically and numerically, showing that fingerprint patterns can be modeled as stationary solutions by appropriate tensor field selection.
Evidence suggests that both the interaction of so-called Merkel cells and the epidermal stress distribution play an important role in the formation of fingerprint patterns during pregnancy. To model the formation of fingerprint patterns in a biologically meaningful way these patterns have to become stationary. For the creation of synthetic fingerprints it is also very desirable that rescaling the model parameters leads to rescaled distances between the stationary fingerprint ridges. Based on these observations, as well as the model introduced by Kücken and Champod we propose a new model for the formation of fingerprint patterns during pregnancy. In this anisotropic interaction model the interaction forces not only depend on the distance vector between the cells and the model parameters, but additionally on an underlying tensor field, representing a stress field. This dependence on the tensor field leads to complex, anisotropic patterns. We study the resulting stationary patterns both analytically and numerically. In particular, we show that fingerprint patterns can be modeled as stationary solutions by choosing the underlying tensor field appropriately.