Anisotropic Interaction Models for Simulating Fingerprint Patterns

Researchers: Martin Burger, José Carrillo, Bertram Düring, Carsten Gottschlich, Stephan Huckemann, Lisa Maria Kreusser, Peter Markowich, Carola Schönlieb

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 (Kücken 2013) we propose a new model for the formation of fingerprint patterns during pregnancy. In this class of anisotropic interaction models 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 (Burger 2018, During 2018). In particular, we show that fingerprint patterns can be modeled as stationary solutions by choosing the underlying tensor field appropriately.

M. Burger, B. Düring, L. M. Kreusser, P. A. Markowich, and C.-B. Schönlieb. Pattern formation of a nonlocal, anisotropic interaction model. Mathematical Models and Methods in Applied Sciences, 28(03):409–451, 2018.
B. Düring, C. Gottschlich, S. Huckemann, L. M. Kreusser, and C.-B. Schönlieb. An Anisotropic Interaction Model for Simulating Fingerprints. arXiv:1711.07417, submitted, 2017.
M. Kücken and C. Champod. Merkel cells and the individuality of friction ridge skin. Journal of Theoretical Biology, 317:229 – 237, 2013.

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