Computer scientists have developed a new face recognition method that works in utter darkness, an advance that may lead to improved surveillance and security technology.
The new technology overcomes some of the limitations of the best face recognition systems available today which only work well using photographs taken in good light without shadows.
Saquib Sarfraz and Rainer Stiefelhagen from the Karlsruhe Institute of Technology, Germany, created a system that analyses dozens of infrared images of a person’s face and then compares them to dozens of images taken in daylight.
The comparisons are made with a computer programme that works using a so-called deep neural network system designed to imitate the function of a human brain, ‘Discovery News’ reported.
The researchers said the deep neural network analysed 4,585 images taken in both infrared and visible light, and was able to establish a match in just 35 milliseconds.
“The presented approach improves the state-of-the-art by more than 10 per cent,” Sarfraz and Stiefelhagen told MIT Technology Review.
The 4,585 images represented 82 people and although the speed of the computer was fast, it was only about 80 per cent accurate and worked best when it had many visible light images to compare with the infrared.
In cases where it had only one visible light image, the system accuracy dropped to 55 per cent.
Researchers suggest that better accuracy is possible with bigger datasets and a more powerful network.