![]() By introducing very slight random warps, the same system they developed was unable to cleanly remove the watermark from the underlying image. That involves making the watermark itself slightly different each time it's used. Happily, the researchers have also made suggestions for more effective techniques that, while giving an end-result that looks the same to the human eye, is far harder for computer vision systems to identify. ![]() None of this is likely to come as welcome news to photographers or others, who rely on watermarking to help police copyright. As long as the watermark graphics are semi-transparent, even complex patterns including lines, color gradients, and shadows can be pulled out, and then readily removed by the system. By giving a machine learning system access to a repository of different images that all use the same watermark – something which can be as simple as pointing it at one of the preview galleries at Shutterstock, Adobe Stock, or other similar sites which sell stock graphics – it can eventually identify the consistent watermark on each. Their solution takes into account the regularity of most watermarks.
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