Geologic features, such as faults, dikes, and contacts appear as lineaments in gravity and magnetic data. The automated coherent lineament analysis and selection (ACLAS) method is a new approach to automatically compare and combine sets of lineaments or edges derived from two or more existing enhancement techniques applied to the same gravity or magnetic data set. ACLAS can be applied to the results of any edge-detection algorithms and overcomes discrepancies between techniques to generate a coherent set of detected lineaments, which can be more reliably incorporated into geologic interpretation. We have determined that the method increases spatial accuracy, removes artifacts not related to real edges, increases stability, and is quick to implement and execute. The direction of lower density or susceptibility can also be automatically determined, representing, for example, the downthrown side of a fault. We have evaluated ACLAS on magnetic anomalies calculated from a simple slab model and from a synthetic continental margin model with noise added to the result. The approach helps us to identify and discount artifacts of the different techniques, although the success of the combination is limited by the appropriateness of the individual techniques and their inherent assumptions. ACLAS has been applied separately to gravity and magnetic data from the Australian North West Shelf; displaying results from the two data sets together helps in the appreciation of similarities and differences between gravity and magnetic results and indicates the application of the new approach to large-scale structural mapping. Future developments could include refinement of depth estimates for ACLAS lineaments.