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Functional Technologies had just successfully secured contract commissioned by the Home Office to develop a set of digital forensic tools aiming at image classification and content integrity verification and source inference.


The R&D team at Functional Technologies recently developed in new patent (UK patent application GB1515615.1) on object clustering method, which is capable of clustering patterns in a large database with the number of classes far greater than the size of the classes. To our best knowledge, this is currently the only method that is able to deal with this problem.


Functional Technologies's research capacity has again led to its success in winning the third TSB Feasibility Studies award in 2013, which will support it to prove a new concept of human-computer interaction.


Following last year's successful bid for a TSB Feasibility Studies award, Functional Technologies has won another this year to conduct research into the feasibility of devising a compact attribute set of camera fingerprint for a wide range of forensics applications.


After a rigorous process of review and interview, our product, Forensic Image Analyser (developed for our client Forensic Pathways Ltd), stood out as a medalist for the Technology Excellence Awards categories of 2011 UK IT Industry Awards presented by the British Computing Society. The Chief Executive Officer of BCS, David Clarke, MBE quotes: "The awards are very rigorously judged so to be a winner or medallist means that you really are the best of the best."


Forensic Imaging in Reverse? Functional Technologies' recent achievement is covered at BCS website.


Functional Technologies has been shortlisted for the 2011 UK IT Industry Award - one of the most prestigious awards presented annually by the British Computing Society . The winners will be announced on 10 November 2011. The company’s entry to the award competition is the Forensic Image Analyser (FIA) developed for our client. FIA is capable of using the enhanced sensor pattern noise (SPN) extracted from images as device signature to identify the source devices, verify content integrity and blindly classify images into groups such that each group corresponds to an unknown device. The novelty of this product lies in the Sensor Pattern Noise Enhancer, which is currently the only method capable of preventing scene details from distorting the SPN and facilitating the afore-mentioned forensic applications effectively.


Functional Technologies has been awarded a prestigious Feasibility Studies grant by the Technology Strategy Board to conduct research into the methodologies for dealing with demosaicking distortion (i.e., error due to colour interpolation during the image acquisition process) to the "fingerprint" left in photos by the imaging devices. The methodologies will allow "cleaner" device fingerprints to be extracted from photos for various forensics applications such as source device identification and content integrity verification.