Victory Sign Biometric for Terrorists Identification

TL;DR

This paper introduces a novel biometric method for identifying individuals, especially terrorists, based on their victory sign hand gesture, using geometric features and Hu Moments extracted from images captured by a mobile phone camera.

Contribution

It presents the first investigation into using victory sign hand gestures as a biometric identifier and develops a new database for this purpose.

Findings

Identification accuracy ranged from 40% to 93%.

Geometric features and Hu Moments provided promising results.

KNN classifier effectiveness varied with features and parameters.

Abstract

Covering the face and all body parts, sometimes the only evidence to identify a person is their hand geometry, and not the whole hand- only two fingers (the index and the middle fingers) while showing the victory sign, as seen in many terrorists videos. This paper investigates for the first time a new way to identify persons, particularly (terrorists) from their victory sign. We have created a new database in this regard using a mobile phone camera, imaging the victory signs of 50 different persons over two sessions. Simple measurements for the fingers, in addition to the Hu Moments for the areas of the fingers were used to extract the geometric features of the shown part of the hand shown after segmentation. The experimental results using the KNN classifier were encouraging for most of the recorded persons; with about 40% to 93% total identification accuracy, depending on the features, distance metric and K used.