This isn't foolproof, so the scanner will try several different options if more than three locators are found. Since this hourglass property could be true of other symbol combinations (like any of #5-8 corner-to-corner) we additionally check for an empty space in the center of the image to confirm. Just like the squares of a QR code, we can use this to determine the location of the corners and thus the dimensions of the grid. The hourglass symbols (13 and 14) are used as locators because they have an interesting property - if you scan two perpendicular lines through the center, the vertical line will be one color and the horizontal line will be the opposite color. Since any of the four triangles can be on or off, that gives us 16 possible symbols: Each cell is divided corner-to-corner into four triangles. The image is a 9x9 grid of cells with three corner locators, an empty cell in the middle, and an empty cell next to the third locator. Now that you know what to look for, you might notice some of these same features in the image at the head of this article. And there are a lot more details you can learn about in the QR Code Wikipedia page. This is why you see a lot of QR codes with logos in the middle - they exploit this self-correction. QR also has error correction (in the form of variable Reed-Solomon encoding) that unlike UPC's check digit can recover from damaged data. And just like UPC, those locators don't appear in the data. Now that you know where the corners are, you can map a grid and read the data. Those square-in-a-square locators will allow you to find their center point looking for a 1:1:1:3:1:1:1 pattern of alternating black and white in the horizontal and vertical directions. You start by just scanning line-by-line down your image. The thing that surprised me when learning about QR (by reading the commonly used and cleverly named Zebra Crossing barcode scanning library) is that 2D codes are built on the fundamentals of 1D scanning. The three boxes in the corners are locators, and they're kind of clever. Here's a QR code that encodes the same 12 digits as the above UPC. Let's move on to 2D codes and explore a QR code. There are a lot more interesting details I won't go into but if you're really interested, Wikipedia has a good explanation. Also, the 12th digit is actually a check digit used to detect a misread code. If it did, the data could be mistaken for the start/end and you'd get a garbled result. The start/end markers are an important feature, but it's also important that the start/end marker pattern doesn't occur in the data. Once you have the boundaries and the resolution, you can turn the signal into a sequence of bits and then into the numbers in the UPC. This delimits the bounaries of the code and gives a reference point to calculate the pulse resolution. If we treat the black bars as a high level and white as low, the signal returned as we scan left-to-right across that line will look like this:Īt the beginning and end are a marker pattern. When a UPC is scanned, what's actually happening is a line is scanned across the image, and a sequence of light/dark segments is reported. It encodes a 12 digit number as a series of light and dark bars. For example, the ubiquitous Universal Product Code, or UPC. One Dimensionīefore we look at 2D codes, let's talk about how one-dimensional codes work. Then we'll get into all the gritty details of the Semaphor Code. It looks like this:īut how does that work? How does the receiver detect and decode the symbols? What does it actually contain? Let's dive in by first exploring the fundamentals of optical scanning. It looks kind of like a QR code, but it's made out of the triangular shapes that make up the SpiderOak product branding design. If you've used Semaphor, you've probably noticed a different kind of optical code used for setting up accounts on mobile devices.
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