To clearly identify the surface streamlines of ships and accurately reflect the characteristics of ship flow fields, a differential streamline seed point selecting algorithm based on ship partition and ship surface feature values is proposed for ship surface features, which achieves encrypted selection of seed points in complex flow field areas. A spatially uniform selection algorithm is proposed for overly dense seed points, combined with information entropy for optimal selection of seed points. By choosing different ship types, different seed point selection algorithms, and streamline effect judgment criteria, the streamline effect is compared and verified to prove the effectiveness and superiority of the algorithm proposed in this paper.