Imaging Components, Systems, and Processing

Threat assessment using visual hierarchy and conceptual firearms ontology

[+] Author Affiliations
Abdullah N. Arslan

Texas A&M University-Commerce, Ontological Semantic Technology Laboratory, Commerce, Texas 75428, United States

Texas A&M University-Commerce, Department of Computer Science and Information Systems, Commerce, Texas 75428, United States

Christian F. Hempelmann

Texas A&M University-Commerce, Ontological Semantic Technology Laboratory, Commerce, Texas 75428, United States

Texas A&M University-Commerce, Department of Literature and Languages, Commerce, Texas 75428, United States

Salvatore Attardo

Texas A&M University-Commerce, Ontological Semantic Technology Laboratory, Commerce, Texas 75428, United States

Texas A&M University-Commerce, College of Humanities, Social Sciences and Arts, Commerce, Texas 75428, United States

Grady Price Blount

Texas A&M University-Commerce, College of Science, Engineering, and Agriculture, Commerce, Texas 75428, United States

Nikolay Metodiev Sirakov

Texas A&M University-Commerce, Ontological Semantic Technology Laboratory, Commerce, Texas 75428, United States

Texas A&M University-Commerce, Department of Mathematics, Commerce, Texas 75428, United States

Texas A&M University-Commerce, Department of Computer Science and Information Systems, Commerce, Texas 75428, United States

Opt. Eng. 54(5), 053109 (May 13, 2015). doi:10.1117/1.OE.54.5.053109
History: Received January 11, 2015; Accepted March 31, 2015
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Abstract.  The work that established and explored the links between visual hierarchy and conceptual ontology of firearms for the purpose of threat assessment is continued. The previous study used geometrical information to find a target in the visual hierarchy and through the links with the conceptual ontology to derive high-level information that was used to assess a potential threat. Multiple improvements and new contributions are reported. The theoretical basis of the geometric feature extraction method was improved in terms of accuracy. The sample space used for validations is expanded from 31 to 153 firearms. Thus, a new larger and more accurate sequence of visual hierarchies was generated using a modified Gonzalez’ clustering algorithm. The conceptual ontology is elaborated as well and more links were created between the two kinds of hierarchies (visual and conceptual). The threat assessment equation is refined around ammunition-related properties and uses high-level information from the conceptual hierarchy. The experiments performed on weapons identification and threat assessment showed that our system recognized 100% of the cases if a weapon already belongs to the ontology and in 90.8% of the cases, determined the correct third ancestor (level concept) if the weapon is unknown to the ontology. To validate the accuracy of identification for a very large data set, we calculated the intervals of confidence for our system.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Topics

Firearms ; Weapons

Citation

Abdullah N. Arslan ; Christian F. Hempelmann ; Salvatore Attardo ; Grady Price Blount and Nikolay Metodiev Sirakov
"Threat assessment using visual hierarchy and conceptual firearms ontology", Opt. Eng. 54(5), 053109 (May 13, 2015). ; http://dx.doi.org/10.1117/1.OE.54.5.053109


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