On Identifying Terrorists Using Their Victory Signs

Authors

DOI:

https://doi.org/10.5334/dsj-2018-027

Keywords:

hand geometry, hand segmentation, terrorist identification, victory sign, hand shape biometric

Abstract

In certain cases, the only evidence to identify terrorists, who are seen in digital images or videos is their hands’ shapes, particularly, the victory sign as performed by many of them when they intentionally hide their faces, and/or distort their voices. This paper proposes new methods to identify those persons for the first time from their victory sign. These methods are based on features extracted from the fingers areas using shape moments in addition to other features related to fingers contours. To evaluate the proposed methods and to show the feasibility of this study we have created a victory sign database for 400 volunteers using a mobile phone camera. The experimental results using different classifiers show encouraging identification results; as the best precision/recall were achieved by merging normalized features from both methods using linear discriminate analysis classifier with 96.6% precision and 96.3 recall. Such a high performance achieved by the proposed methods shows their great potential to be applied for terrorists’ identification from their victory sign.

Author Biography

Ahmad B. A. Hassanat, IT Department, Mutah University, Karak

Ahmad B. A Hassanat was born and grew up in Jordan, received his Ph.D. in Computer Science from the University of Buckingham at Buckingham, UK in 2010, and B.S. and M.S. degrees in Computer Science from Mutah University/Jordan and Al al-Bayt University/Jordan in 1995 and 2004, respectively. He has been a faculty member of Information Technology department at Mutah University since 2010. His main interests include computer vision, Machine learning, Big data and pattern recognition.

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Published

2018-10-15

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Section

Research Papers