Identification of partially occluded firearms through partonomy

Abdullah N. Arslan; Christian F. Hempelmann; Salvatore Attardo; Grady Price Blount; Nona N. Sirakova; Nikolay Metodiev Sirakov

doi:10.1117/12.2184102

28 May 2015 Identification of partially occluded firearms through partonomy

Abdullah N. Arslan, Christian F. Hempelmann, Salvatore Attardo, Grady Price Blount, Nona N. Sirakova, Nikolay Metodiev Sirakov

Author Affiliations +

Proceedings Volume 9476, Automatic Target Recognition XXV; 94760U (2015) https://doi.org/10.1117/12.2184102
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

Abstract

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.

Citation Download Citation

Abdullah N. Arslan, Christian F. Hempelmann, Salvatore Attardo, Grady Price Blount, Nona N. Sirakova, and Nikolay Metodiev Sirakov "Identification of partially occluded firearms through partonomy", Proc. SPIE 9476, Automatic Target Recognition XXV, 94760U (28 May 2015); https://doi.org/10.1117/12.2184102

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE