While network models of porous materials have traditionally been constructed using regular or disordered lattices, recent developments allow the direct modeling of more realistic structures such as sphere packings, microtomographic images, or computer-simulated materials. One of the obstacles in these newer approaches is the generation of network structures that are physically representative of the real systems. In this paper, we present and compare two different algorithms to extract pore network parameters from three-dimensional images of unconsolidated porous media systems. The first approach, which utilizes a pixelized image of the pore space, is an extension to unconsolidated systems of a medial-axis based approach (MA). The second approach uses a modified Delaunay tessellation (MDT) of the grain locations. The two algorithms are validated using theoretical packings with known properties and then the networks generated from random packing are compared. For the regular packings, both methods are able to provide the correct pore network structure, including the number, size, and location of inscribed pore bodies, the number, size, and location of inscribed pore throats, and the connectivity. Despite the good agreement for the regular packings, there were differences in both the spatial mapping and statistical distributions in network properties for the random packings. The discrepancies are attributed to the pixelization at low resolution, non-uniqueness of the inscribed pore-body locations, and differences in merging processes used in the algorithms, and serve to highlight the difficulty in creating a unique network from a complex, continuum pore space.