Digital image processing was recently proved to be successfully approached by
variational tools, which extend the Casseles-Kimmel-Sapiro weighted length
problem. Such tools essentially lead to the socalled Geodesic Active Flow
(GAF) process, which relies on the derived mean curvature flow PDE. This
prolific process is valuable due to both the provided numeric mathematical
insight, which requires specific nontrivial choices for implementing the
related algorithms, and the variety of possible underlying specific
geometric structures. A natural Finsler extension of Randers type was
recently developed by the authors, which emphasizes the anisotropy given by
the straightforward gradient, while considering a particular scaling of the
Lagrangian. The present work develops to its full extent the GAF process to
the Randers Finslerian framework: the evolution equations of the model are
determined in detail, Matlab simulations illustrate the obtained theoretic
results and conclusive remarks are drawn. Finally, open problems regarding
the theoretic model and its applicative efficiency are stated.