Identification of partially occluded firearms through partonomy

In the present paper we study the problem of weapon identification and threat assessment from a single image with a partially occluded weapon. This problem poses very severe restrictions. To successfully identify a weapon from its parts we extend the first firearm ontology with the meronymic (partonomic) principle which lets us distinguish parts of a gun (e.g., lock, barrel, stock, scope). Adding classes of meronymic information provides meta-data (necessary for threat assessment) and allows for fast and accurate search. Searching for a weapon is treated conceptually as searching for the sum of its parts. An expanding active contour and morphological techniques are applied to partition weapons and extract boundaries, and a minimal inscribed complex polygon. Finite numerical sequences are generated, from the extracted geometric features, and are used to label partonomic nodes and perform quick and accurate search. The paper reports experimental results on weapons partitioning and search.