Thread

Apple Reference Image: A New Approach for Verified Photography

539 points · 352 comments · imwally

tristanj · 1789527436 · focus · HN ↗
Apple doesn't address the modified photo replay situation, where you take a picture of an already edited image.
Photoshop / AI-gen an image -> display on a high-resolution monitor -> photograph the monitor with iPhone 18 Pro -> valid Apple Reference image.
To get valid reference photos, you can go to the actual physical location, put the iPhone/monitor in a cardboard box to block external light, then photograph the monitor. Paint the inside of the box using Vantablack (stopping reflections) and cover the LiDAR projector with tape.
I can't wait to see Apple Verified™ photos of UFOs flying over the Golden Gate Bridge.
1. pveierland · 1789528538 · focus · HN ↗
  Claim 7 in this patent application describes how depth sensors are used as part of an image authentication process, which would make such a workaround more difficult:
  <a href="https://image-ppubs.uspto.gov/dirsearch-public/print/downloadPdf/20260268025" rel="nofollow">https://image-ppubs.uspto.gov/dirsearch-public/print/downloa...
  The Apple Reference Image feature is here launched on iPhone 18 Pro and iPhone 18 Pro Max that both have built-in LiDAR sensors that could be used for this process.
  1. tristanj · 1789529371 · focus · HN ↗
    Apple's current implementation doesn't integrate LiDAR. And LiDAR wouldn't be enough here, it's trivial to block the projector and hide the dot pattern. No dot pattern = iPhone thinks the object is far away, which is what happens in landscape photos.
    A better fix is to take photos with all three iPhone cameras simultaneously, ideally as a 2-3s video, and use the parallax/multiple perspectives to extract depth information. The video files (Possibly audio too) could also be included with the verified image as additional verification.
    They can also prevent photos if iPhone detects the LiDAR sensor is covered, similar to how Meta does it with their camera glasses.
    pveierland · 1789529702 · focus · HN ↗
    I don't think it's an either or - additional data signals that need to correlate to authenticate will increase confidence. You can use multiple other signals to evaluate whether something is truly a landscape photo, and in that case not require a LiDAR capture, but if you are inside and at close range then you could assume that it should be part of scoring the authentication.
    Similarly, LiDAR alone will help disqualify cases where someone is just taking a picture of e.g. a landscape target of the Golden Gate, but that it shown on a screen 1 meter away.
    halestock · 1789530047 · focus · HN ↗
    This approach makes me wonder if the future is actually going to move towards visual cryptography.
    alwillis · 1789537027 · focus · HN ↗
    Um… that's already a thing [1]:
    TL;DR: What is C2PA in 60 seconds What: An open technical standard for embedding cryptographically signed provenance data inside digital media files. Who: Created by a coalition founded by Adobe, Arm, BBC, Intel, Microsoft, and Truepic in February 2021. How: A C2PA Manifest (also called a Content Credential) travels inside the file and records who made it, when, and what tools were used. Why: Deepfake incidents surged from 500,000 to 8 million cases between 2023 and 2025. Provenance gives media a verifiable chain of custody.
    [1]: <a href="https://c2paviewer.com/articles/what-is-c2pa" rel="nofollow">https://c2paviewer.com/articles/what-is-c2pa
    halestock · 1789575013 · focus · HN ↗
    Hm, that's more like digitally signing an image. I'm thinking about something like e.g. encoding/encrypting depth information from multiple images to create a composite that can't be duplicated without the source images.
    sandcat_ · 1789532665 · focus · HN ↗
    Right but I’d argue that realistically this feature is going to be most useful when taking photos of things reasonably close by, people especially, rather than landscape photography.
    dylan604 · 1789535418 · focus · HN ↗
    > it's trivial to block the projector and hide the dot pattern. No dot pattern = iPhone thinks the object is far away, which is what happens in landscape photos.
    I've never looked at the LiDAR hardware, but where is the emitter in relation to the receiver. Why would the LiDAR not reflect off of whatever you're blocking it with and return a very short flight meaning it was very close?
    jojobas · 1789537149 · focus · HN ↗
    Paint the stopper vantablack then.
    testdelacc1 · 1789539833 · focus · HN ↗
    I knew keeping a pot of vantablack in my jacket pocket would come in handy.
    mitxela · 1789552949 · focus · HN ↗
    I think the plan is to block the emitter, not the emitter and the receiver together
    Findecanor · 1789549829 · focus · HN ↗
    > all three iPhone cameras simultaneously, ideally as a 2-3s video, and use the parallax/multiple perspectives to extract depth information.
    I think optics could be used to make each camera see a different image.
    A video could show shake, which could be verified against readings from the phone's accelerometer -- but you could just hold it still and claim that it was on a tripod.
    avianlyric · 1789583386 · focus · HN ↗
    > A better fix is to take photos with all three iPhone cameras simultaneously, ideally as a 2-3s video, and use the parallax/multiple perspectives to extract depth information.
    I think iPhones already do this (although without taking multiple seconds of video). iOS is capable of generating pretty accurate depth data even on devices with no LiDAR unit.
    astafrig · 1789654714 · focus · HN ↗
    Using the cameras to estimate depth information is not really a better solution than using the LiDAR sensor because the cameras are so close together that the effective range for parallax depth estimation and the effective range of the LiDAR sensor are very similar.

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