Image searches

by Stubborn Mule on 12 July 2012 · 10 comments

This week’s edition of Media Watch, “Pixelating protects identity? Think again“, examines the threat image search engines pose to anonymity. Drop a disguised photo into Google images and the chances are you will find the original in the search results.

Intrigued, I thought I would try it out. The pixellated the photo of Tom Waits was my second test. The first image I found to try was a golden pyramid. (It is from a presentation I recently pulled together on cognitive dissonance, but that is unlikely to be a helpful explanation).


In this case the search results came close to being artistic: an impressive array of alternative golden pyramids.


I can see that Google images could be rather fun.

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{ 10 comments… read them below or add one }

1 Magpie July 13, 2012 at 9:59 am

Well, I’ll be damned…

Some friends I have are used to make fun of my “paranoia”. I’ll see to it they watch this segment, just so I can ask them who’s laughing now?

2 Stubborn Mule July 13, 2012 at 12:12 pm

Laughing magpie?

3 Magpie July 13, 2012 at 2:32 pm

And squawking, too!

4 Golden Orb July 13, 2012 at 8:32 pm

It picked up the strangely edible texture of your pyramid, which is even more impressive than picking up the missing bits of Tom’s face.

5 Stubborn Mule July 13, 2012 at 8:49 pm

@Golden Orb: shades of Toblerone? Mind you, not sure how edible the scrubbing brushes, bottom right are!

6 Ken July 16, 2012 at 7:23 pm

It would be interesting to know what there algorithms do. A reasonable engineering starting point would be to perform fourier transforms on the full image and selected sub images. Then restructure the output so that it is in order of major of major to minor features, so that comparisons are fast, as they stop if major features are not in common. Then all you need is to determine a measure of how close the images are. Presumably all the pixelated images are matching well on sub images, and giving some commonality to the overall image. These days there are lots of other options like fractals and hidden markov models to do what is effectively dimension reduction.

7 Golden Orb July 21, 2012 at 11:41 am

Would it then be able to match, say, a pixelated single face taken from a group shot? Or only if the overall pictures are the same?

It seems to have quite a high tolerance for error, which could positively match the wrong person. Although it is somewhat heartening that it puts up several options if it is unsure.

8 Stubborn Mule July 21, 2012 at 1:43 pm

@Golden Orb: I haven’t experimented with group shots, but I suspect it may fail. What I have tried was submitting a photo of my own face. It was a photo which is not online anywhere and the suggestions Google came up with were rather amusing!

9 Ken July 21, 2012 at 4:40 pm

One possibility is that they look at sub images, so as to allow for cropping.

10 Thomas July 8, 2013 at 4:23 am

It appears it gets the colors and shades farily accurately. However, geometric shapes show much more variance… Interesting experiment.

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