Ahmad Hassanat from Mu'tah University in Jordan and colleagues have developed a way to distinguish people from the unique way they make the "victory" sign.
The team photographed the V sign made by 50 men and women of various ages with their right hand several times against a black background using an 8-megapixel camera phone, and produced a database of 500 images. Hassanat and colleagues limited their analysis to determining the end points of the two fingers, the lowest point in the valley in between them, and two points in the palm of the hand. They also analyzed the shape of the hand using several statistical measures, and the two approaches created 16 features that can be used in identification. The team then used 66 percent of the images to train a machine-learning algorithm to recognize different V signs and used the remaining images to test its efficacy.
Hassanat says the algorithm was able to distinguish people with an accuracy of more than 90 percent in some cases. He thinks that combined with other data, the approach could be used to identify mask-wearing terrorists making the victory sign.
From Technology Review
View Full Article
Abstracts Copyright © 2016 Information Inc., Bethesda, Maryland, USA
No entries found