What Happens When A Frozen QR Finally Dries

Data Representation, Printmaking

Here’s a quick cellphone pic of the final monotype that resulted when the melted ice cubes of ink used in the frozen QR project finally dried, after four days:

Frozen_QR_Code_Final_Quick

I tacked it up to the pressroom door of the Bow and Arrow Press, so it could relax and flatten a little. I’ll trim the paper down after a while. The ink I used, Higgins Eternal, is archival but not waterproof, so I’ll probably hit this with some Crystal Fixativ later.

Tenth Round of QRs in the Wild

Composites, Data Representation

300… I’ve captured 300 QRs. Here’s the group average, as shot:

(the graininess comes from the fact I photographed three or four QRs on computer monitors this time around)

Generated average:

Average of all 300, as shot–

And all 300, freshly generated:

Since 300 is a big and round number, I figured I’d do another breakdown of the QRs by size, generating averages that are slightly more meaningful because there’s greater overlap. (Here’s the first one.) First, the histogram of QR sizes (given in pixels on the bottom axis):

For the pixel sizes with more than one entry, here are those composites:

216 pixels:

248 pixels:

280 pixels:

312 pixels:

344 pixels:

376 pixels:

408 pixels:

504 pixels:

These averages clearly show the control blocks, the orientation blocks, and the data fields used int he QR specification.

Time Lapse Frozen QR

Data Representation, Time-Lapse

Right now this is a placeholder for a project coming to fruition when the weather gets reliably below freezing.

Here’s a hint to the coming content.

And here’s a shot of the project in process–

Frozen-QR-Time-Lapse

And finally, the finished piece:

The QR code was constructed out of over 300 black pixels made of a frozen mixture of ink and water. They were placed on several sheets of 33″ x 42″ Rives BFK, in case a nice secondary piece of art would emerge once the ink finished drying. I used the vestibule of the Bow and Arrow Press to construct the code, because I could close the two doors connecting to the press room and the cutting room, leaving the outside door open and keeping the vestibule at a nice 20ยบ so the pixels wouldn’t melt until I wanted them to. The time-lapse was done in five-second intervals with a Canon Rebel T2i.

Here are some setup shots:

Setting the Pixels Leftover_Pixels Starting_Shot

Ninth Round of QRs in the Wild

Composites, Data Representation

The sad thing is, I’d had the eighth round mostly processed for a couple months, and I finally finished it up and posted it because I’d collected enough for the ninth round. So… here’s the ninth round! 270 QRs found in the wild.

9th round as-shot

9th round as clean, regenerated codes

Full set of 270 codes, as-shot

Full set of 270, clean, regenerated codes.

Oopsie… Mis-mounted QR Code

Data Representation

I’ve been collecting more QR codes in the wild for my ongoing QR code project (alas, the eighth iteration is done but I haven’t had time to process the images), and found this interesting sample in Manchester, NH, last weekend. It’s great that this company is trying to connect with the whole Web 2.0 dynamic, but they didn’t check the orientation of their sign. The small locator square is supposed to be in the lower right-hand corner, according to the QR definition. I’m sure that phone QR readers are smart enough to decipher the code despite inadvertent rotation, but it’s amusing that people are still making high-profile mistakes like this.

The correct orientation:

QR Averages Based on Pixel Dimensions

Averages, Data Representation

So the averages I’ve been producing have been normalized to one specific size, in this case, 2400 x 2400 pixels for the generated, clean QRs. However, the actual encoded pixel width of the QR depends on how much data one wishes to encode. If you look at any of the composites I’ve done, you see that the anchoring squares come in various sizes, creating a blurry perspective effect in the saved composite.

To generate “clean” averages, then, I would need to sort the QRs by size and produce averages off those subsets. Which is what I did. Here’s a quick histogram of the QR sizes I have, using today’s set of 180 total QRs:

This is something of a “long tail” graph, with a big bulge in the smaller sizes and very few in the larger sizes. In fact, the three largest sizes only have one member each, which means no composite is possible. Those I will not include. The rest, however, I did composite, and the results are here:

216 pixels:

248 pixels:

280 pixels:

312 pixels:

344 pixels:

376 pixels:

408 pixels:

Notice how crisp the anchoring areas of the QR graphic are now, as opposed to the data areas, which vary with each QR. Alas, none of these “clean” composites actually goes anywhere, at least not with the QR reader on my phone.

Sixth Round of QRs in the Wild

Composites, Data Representation

Another set of QR codes discovered lurking in the Real World. Fun fact: one of the codes used I used myself at Somerville Open Studios as a way for people to sign in to my email list. Unfortunately, only three people actually used it: one was an abject failure, one didn’t enter his email address, so only one person actually used Web 2.0 personal digital content in the way it was intended. Here’s the QR:

And here are the as-shot and generated QRs, numbers 151 through 180:

And the composites from the entire set of 180: