Researchers at University College London have devised a software algorithm able to scan and replicate almost anyone's handwriting
In a world increasingly dominated by the QWERTY keyboard, computer scientists at University College London (UCL) have developed software which may spark the comeback of the handwritten word, by analysing the handwriting of any individual and accurately replicating it. The scientists have created "My Text in Your Handwriting" – a programme which semi-automatically examines a sample of a person's handwriting that can be as little as one paragraph, and generates new text saying whatever the user wishes, as if the author had handwritten it themselves. "Our software has lots of valuable applications," says lead author, Dr Tom Haines. "Stroke victims, for example, may be able to formulate letters without the concern of illegibility, or someone sending flowers as a gift could include a handwritten note without even going into the florist. It could also be used in comic books where a piece of handwritten text can be translated into different languages without losing the author's original style." Published in ACM Transactions on Graphics, the machine learning algorithm is built around glyphs – a specific instance of a character. Authors produce different glyphs to represent the same element of writing – the way one individual writes an "a" will usually be different to the way others write an "a". Although an individual's writing has slight variations, every author has a recognisable style that manifests in their glyphs and spacing. The software learns what is consistent across an individual's style and reproduces this.
To generate an individual's handwriting, the software analyses and replicates the author's specific character choices, pen-line texture, colour and the inter-character ligatures (the joining-up between letters), as well as vertical and horizontal spacing. Co-author, Dr Oisin Mac Aodha (UCL Computer Science), said: "Up until now, the only way to produce computer-generated text that resembles a specific person's handwriting would be to use a relevant font. The problem with such fonts is that it is often clear that the text has not been penned by hand, which loses the character and personal touch of a handwritten piece of text. What we've developed removes this problem and so could be used in a wide variety of commercial and personal circumstances." The system is flexible enough that samples from historical documents can be used with little extra effort. Thus far, the scientists have analysed and replicated the handwriting of such figures as Abraham Lincoln, Frida Kahlo and Arthur Conan Doyle. Infamously, Conan Doyle never actually wrote Sherlock Holmes as saying, "Elementary my dear Watson" but the team have produced evidence to make you think otherwise. To test the effectiveness of their software, the research team asked people to distinguish between handwritten envelopes and ones
created by their automatic software. People were tricked by the computer-generated writing up to 40% of the time. Given how convincing it can be, some may believe this method could help in forging documents – but the team explained it works both ways and could actually help in detecting forgeries. "Forgery and forensic handwriting analysis are still almost entirely manual processes – but by taking the novel approach of viewing handwriting as texture-synthesis, we can use our software to characterise handwriting to quantify the odds that something was forged," explained Dr Gabriel Brostow, senior author. "For example, we could calculate what ratio of people start their 'o's' at the bottom versus the top and this kind of detailed analysis could reduce the forensics service's reliance on heuristics."Computer program learns to replicate human handwriting
created by their automatic software. People were tricked by the computer-generated writing up to 40% of the time. Given how convincing it can be, some may believe this method could help in forging documents – but the team explained it works both ways and could actually help in detecting forgeries. "Forgery and forensic handwriting analysis are still almost entirely manual processes – but by taking the novel approach of viewing handwriting as texture-synthesis, we can use our software to characterise handwriting to quantify the odds that something was forged," explained Dr Gabriel Brostow, senior author. "For example, we could calculate what ratio of people start their 'o's' at the bottom versus the top and this kind of detailed analysis could reduce the forensics service's reliance on heuristics."Computer program learns to replicate human handwriting
