We have developed an optimization method for automatic dyke delineation from observed magnetic gradient traverse data. A non-linear least squares algorithm is used to find model dyke parameters that best fit the computed gradient tensor data to the observed data. The problem of encountering local minima during the inversion makes it imperative to find good starting parameters for the model. We determine such starting parameters on the basis of the eigen-properties of the observed gradient data, assuming a dyke model of constant cross-section and infinite strike extent. The method works well on synthetic examples. A real case study with remanence, taken from the Platreef, shows that the gross observed gradient features can be recovered by such a model, but the residuals in the gradient fit hint strongly to a need for more complex dyke models.