Understanding the processes and mechanisms that control preferential flow in soils in relation to the properties of their structures is still challenging since fast flow and transport occur in a small fraction of the porosity, that is, the functional macropore network, making it difficult to image and characterize these processes at decimeter scales. The aim of the paper was therefore to propose a new image acquisition and analysis methodology to characterize preferential flow at the core scale and identify the resulting active macropore network. Water infiltration was monitored by a sequence of three-dimensional images (taken at 5-, 10-, or 15-min intervals) with an X-ray scanner that allows very fast acquisitions (10 s for a 135-mm diameter). A simultaneous dye tracer experiment was also conducted. Water infiltration was then imaged at each acquisition time by the voxels impacted by water during infiltration, named the water voxels. The number of times a voxel was impacted by water during the experiment was converted into data reflecting the water detection frequency at the given position in the soil column, named the local detection frequency. Compared with dye staining, the active macropore network was defined by macropores in which water voxels were the most frequently detected during the experiment (local detection frequency above 65%). The geometric properties of this active network, such as the connectivity, were significantly different from those of the total structure. This image processing methodology coupled to dynamic acquisitions can be used to improve the analysis of preferential flow processes related to soil structures at the core scale.