How It Works
Introduction
Knowing who owns digital content (e.g., images, videos, etc.) on the internet is an important problem. For content creators (e.g., artists, photographers, etc.) and media management companies (e.g. Getty images, Shutterstock, etc.), the sale of licenses is the primary way in which they are compensated. However, once the image or video is published on a website or web application, it’s difficult to stop others from simply downloading and reusing it without paying for the license.
One of the traditional ways in which companies try to solve this problem is by crawling the internet, looking for license violations. However, crawlers rely on being able to match candidate violations to a database. This solution is imperfect because it is easy to edit images and videos in programs like Photoshop, and once the image is edited, it becomes far more difficult to match to the database (and prove that it is a derivative of the original content). Another possible solution is to use metadata to store ownership/copyright information; however, metadata is easily stripped.
Using cutting edge watermarking technology, Steg AI offers a new solution to this ownership/copyright problem. In particular, Steg AI invisibly watermarks digital media with unique identifying information that can be used to trace any asset back to the owner and licensee. These watermarks can not be stripped by removing the metadata and are robust to edits. Moreover, we integrate with Drives (e.g., OneDrive, Google Drive) and Digital Asset Management (DAM) companies to keep the process simple and to keep the digital assets in their original location.
Steg AI’s Invisible Watermarks
Steg AI uses proprietary deep learning technology that we develop in-house to invisibly watermark digital content (e.g., images, videos, documents, audio, etc.). These watermarks perturb the data itself to bake information into that data. That information can be anything the user wants; for example, basic information like author and license and complex information like the meeting in which the asset was shared and the people that were there.
The figure below shows an example of the watermarking technology being applied to an image. The image on the left is the original and the image on the right is the watermarked version.
With images, the pixels represent the underlying data and our watermark is baked into those pixels through small perturbations in intensity values. One big positive of this approach is that the watermark is nearly impossible to remove. For example, removing the metadata of the image has no impact on the watermark whatsoever, and the watermark will survive more complex image manipulations like cropping, enveloping, occlusions, blur, color shifts, etc.
For more information on Steg AI watermarking, check out the Technology section of the Steg AI website.
Using Steg AI Watermarking Technology for Copyright Protection
Steg AI watermarks imbue assets with unremovable, yet imperceptible ownership/copyright information. The key is that each time a digital asset is licensed, a new, unique watermark is applied to that asset. The watermark stores the ownership information and cannot be easily removed. Then, any time ownership comes into question, we read the watermark to retrieve the license. This process can be broken into two steps.
Step 1: Apply the watermark to imbue ownership.
The figure below outlines a flow we find often works for our customers. First, most stock media companies have a web application to display and sell media. Using our API, we can easily integrate into those web applications. Then, anytime an asset is licensed, we watermark that asset to imbue that asset with the customer’s license information. In the figure, the blue, yellow, and green customers license the mountain image and each receives a uniquely watermarked version. Similarly, the red and magenta customers both license the castle video and receive uniquely watermarked versions.
Step 2: Catch unlicensed use.
The licensed assets are now in the hands of customers and will soon be published on the internet in one form or another. It’s only a matter of time before these assets are downloaded, possibly edited, and reused without license. Without Steg AI, there would be no way of figuring out the origin and ownership of those assets; but, with Steg AI, there is a solution.
If you are able to find these assets yourself, then you can simply download the asset and use Steg AI to read the watermark and retrieve the license information. However, in many cases, it is unclear where the assets are being used without permission. Thus, Steg AI works with web crawling partners to scan the internet for potential misuse. In particular, the web crawlers scan commercial websites looking for potential assets. Steg AI then attempts to read watermarks from these assets and determine if the assets are being used without the proper license. Steg AI then surfaces these incidents back to the owner of these assets, so that the owner can recapture that lost revenue.
Start Using Steg AI Today
There are many ways that the above solution can be adapted to different customer scenarios. Steg AI watermarking and ownership/copyright protection products can be surfaced through our API or Web Application or via integrations with Drives/DAMs or common software workflows like Photoshop plugins. If you are interested in learning more about ownership and copyright protection using Steg AI technology. Please contact us.