The professor is now using sensor pattern noise technology to help Interpol group the 5 million images in its international child exploitation database by source camera. Police identified the fingerprint of the smartphone camera, and by comparing this to the fingerprints of the pornographic video stills, found a match strong enough that the man pleaded guilty and was sentenced to nine years in jail. ‘Initially, the suspect denied his responsibility, and claimed that the two videos were sent to him by someone else,’ he explained. When police arrested a man on suspicion of possessing child pornography and discovered the suspect’s mobile phone held two videos involving children, they turned to Prof. Professor Chang-Tsun Li, of the University of Warwick, led the EU-funded project, a major focus of which was developing multimedia sensor pattern noise extraction technologies. In the UK, a research and industry consortium named DIVeFor has already proved the worth of sensor pattern noise technology in criminal forensics, in 2014 helping Sussex Police to secure the first ever conviction using image fingerprints. Imate digital photo frame software#The team will simultaneously launch the software through a startup company, and hopes to add a parallel product by autumn, which uses the sensor pattern noise from smartphone cameras to offer a simpler alternative to two-step authentication processes like Wi-Fi logins. ToothPic’s technology has already sparked a media forensics collaboration with the Turin Police, while photo marketplaces and photographers seeking their stolen cameras are also interested, he said. Magli notes there are privacy concerns around using this kind of information, he believes such photo fingerprint applications are nothing to be concerned about. The demo - a simple internet app, where people can upload a picture or fingerprint and check if it matches photos in ToothPic’s database - is hoped to attract the attention of social media heavyweights like Google or Facebook, which could theoretically offer an internet-wide fingerprint search service thanks to their extensive image databases. To this end, his team will launch a demonstration search engine this summer, and has a network of about 100 university computers hard at work, downloading 50 million pictures from Flickr. ‘What we do is really to make the fingerprint easily searchable and optimised to make it as fast as possible.’ Professor Enrico Magli, Politecnico di Torino, Italy With more than 350 million pictures also uploaded to Facebook daily, he contends that there needs to be a way to deal with illegal or unethical photo use in this sphere. Magli says copyright infringement is now something of a ‘national sport’ on photo-based social media websites like Flickr. Primarily, ToothPic is zooming in on the potential to verify image copyrights. ‘What we do is really to make the fingerprint easily searchable and optimised to make it as fast as possible.’ ‘What we have in mind with ToothPic is the ability to be able, with a suitably sized data centre, to process millions of pictures per second,’ said Prof. He launched a separate ERC-funded project, known as ToothPic, in late 2015, to look specifically at the camera identification issue. Professor Enrico Magli, of Politecnico di Torino, is using the compression technology of this project, which was funded with a grant from the EU’s European Research Council (ERC), to streamline the identification of the cameras behind online images. For one, the extracted fingerprints dwarf their original images, hindering large-scale sensor pattern noise applications due to the brute computational force and extensive storage space required.īut a team of Italian researchers working on a project named CRISP, developing technology for compressing signals and images in big data, stumbled onto a potential solution. The research enabling the extraction of these weak, but universal traces already emerged in 2006, but several problems remained to be solved. The pixel imperfections of a camera’s sensor leave a unique fingerprint on the images it creates, known as sensor pattern noise. In an ideal world, photographs of a pure blue sky taken by two identical cameras would be indistinguishable. Even with the most advanced manufacturing methods, every camera sensor is not created equal.įor example, a 10 megapixel camera sensor has an array of 10 million pixels - tiny cavities which trap light, turning it into a digital signal - and each of these can vary in how it measures light.
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