COVER STORY • 封面專題 2021 UMAGAZINE 24 • 澳大新語 22 has never been altered, there should be a consistent noise pattern throughout it,’ Prof Zhou says. Since 2019, his team has developed new ways to accurately examine noise and extract features from images, in a project supported by the Macao Science and Technology Development Fund (FDCT). This project has inspired new algorithms for detecting forged images. The Truth in the Details In early 2021, Prof Zhou’s team won the championship in the image forgery track, and the third prize in the detection track, at the Security AI Challenger Contest (Season 5). At this algorithm competition organised by Tsinghua University and Alibaba, the team altered 20 images, such as changing names and dates on ID cards, and added a special adaptive noise. ‘We generated the noise after analysing background details and noise in the authentic parts, in order to hide the forgery traces from AI detection tools. We turned out to be the best forger among the 1,534 teams,’ Prof Zhou says. It has never been easier to create forged images, which are now very convincing. At the University of Macau (UM), the team of Associate Professor Zhou Jiantao in the Department of Computer and Information Science has developed a cutting‑edge algorithm to detect such images. After defeating over 1,500 rivals at an international competition, they have continued to improve the algorithm under a project with the e‑commerce giant Alibaba. Seeing Is Not Believing Prof Zhou is the interim head of UM’s Centre for Artificial Intelligence and Robotics, as well as a member of the university’s State Key Laboratory of Internet of Things for Smart City. ‘In many images, the forged parts are undetectable to the naked eye, sometimes even to computer programmes,’ he says. Like a human detective, a good image forgery detection tool has to recognise details that others might overlook. In digital images, such details include noise and other features. ‘For instance, if an image 周建濤教授運用團隊開發的算法，將一張食品經營許可證被篡改的部分偵測出來。 The algorithm developed by Prof Zhou Jiantaoʼs team can detect the forged parts of an image of a food business licence
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