Head-related transfer functions (HRTFs) depend on the shape of the human head and ears, motivating HRTF personalization methods that detect and exploit morphological similarities between subjects in an HRTF database and a new user. Prior work determined similarity from sets of morphological parameters. Here we propose a non-parametric morphological similarity based on a harmonic expansion of head scans. Two 3D spherical transforms are explored for this task, and an appropriate shape similarity metric is defined. A case study focusing on personalisation of interaural time differences (ITDs) is conducted by applying this similarity metric on a database of 3D head scans.