paulmillr-qr
Minimal browser and node.js QR Code Pattern encoder & decoder.
- 🔒 Auditable, 0-dependency
- 🏞️ Encoding (generating) supports ASCII, term, gif and svg codes
- 📷 Decoding (reading) supports camera feed input, files and non-browser environments
- 🔍 Extensive tests ensure correctness: 100MB+ of vectors
- 🪶 35KB for encoding + decoding, 18KB for encoding (1000 lines of code)
Check out interactive demo paulmillr.com/apps/qr/ and
qrBTF.com, which uses the library to generate custom, styled codes.
Other JS libraries are bad:
- jsQR is dead, zxing-js is dead, qr-scanner uses jsQR and doesn't work outside of browser, qcode-decoder is broken version of jsQR and doesn't work outside of browser, qrcode is fork of jsQR without adoption
- instascan is too big: over 1MB+ (it's zxing compiled to js via emscripten)
Usage
A standalone file paulmillr-qr.js is also available.
npm install @paulmillr/qr
Encoding
import encodeQR from '@paulmillr/qr';
const txt = 'Hello world';
const ascii = encodeQR(txt, 'ascii');
const terminalFriendly = encodeQR(txt, 'term');
const gifBytes = encodeQR(txt, 'gif');
const svgElement = encodeQR(txt, 'svg');
const array = encodeQR(txt, 'raw');
const highErrorCorrection = encodeQR(txt, 'gif', { ecc: 'high' });
const customEncoding = encodeQR(txt, 'gif', { encoding: 'byte' });
const larger = encodeQR(txt, 'gif', { scale: 4 });
console.log(ascii);
> █████████████████████████████████████
> ██ ▄▄▄▄▄ █ ▀▄▄█ ██▀▄▄▄▄█ ▀█ ▄▄▄▄▄ ██
> ██ █ █ █▀▄▀▄ ▄▄█▄█ ██▀█▀▀█ █ █ ██
> ██ █▄▄▄█ ██ ▄▄█▄▀▀ ▀ ██ ▄ ▄█ █▄▄▄█ ██
> ██▄▄▄▄▄▄▄█ ▀ ▀ █▄▀ ▀ ▀▄█ █ █▄▄▄▄▄▄▄██
> ██ █ ▀ ▄▄▀▀▀ █▀ ▄ ▀▀▄▀ ▄█ ▀█ ▀▄▄██
> ██▀▀▀ ▀▄▄██▄▀▀▄█▀ ▀▄█ ▀▀▀ ▄ █▄▄██
> █████▄▀▀▄▄██ ▀ ▀ ▄▄██▄ ▄▄ ▄ █▀█ █ ███
> ███ ▄▀▄█▄▄▄█ ▀██▄▄▄▀▀█▄▀ ▄█▀ ████
> ██▀▀ ▄ ▀▄ ▄▄██▀▄▀▀████▄▄▄ █▄ █ █▀▀██
> ██▀▀▄ ▄▀▄ ▀▀█▄▀▀▄▄▀▀ █▄▄▀█▀ ▀▄ █▄ ▀██
> ██▀▄▀██ ▄▄ ▀█▄█▀ ▀ ▀█▄▀▀ █▄▀▀ █ █ ██
> ███▀█▄▀▄▄ █ █ ██ ██ ▄ █ ▄▄▄ ▄▀▀▄▄ ██
> ██▄█▄▄▄█▄█ ▄ ▄▀█▀▀ ▄▀ █▀ ▄ ▄▄▄ ▀▄▀▄██
> ██ ▄▄▄▄▄ █ ▄█▄▀▀ ▀█ █▄█ █▄█ ▀▀▄▀██
> ██ █ █ █▀ ▄▀█ ██ ▄▄▀██ ▄▄ ▄█ ██
> ██ █▄▄▄█ █▄ ██▀ ▄▄ ▀█ ▄ ▀▄▄█▀██
> ██▄▄▄▄▄▄▄█▄███▄█▄█▄▄▄▄█▄█▄████▄▄█████
> ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀
Decoding
GIF reader is not included in the package (it would take a lot of space).
Decoding raw bitmap is still possible.
import encodeQR from '@paulmillr/qr';
import decodeQR from '@paulmillr/qr/decode.js';
import { Bitmap } from '@paulmillr/qr';
const opts = { scale: 4 };
function decodeRawBitmap() {
const bmBits = encodeQR('Hello world', 'raw', opts);
const bm = new Bitmap({ width: bmBits[0].length, height: bmBits.length });
bm.data = bmBits;
const decoded = decodeQR(bm.toImage());
console.log('decoded(pixels)', decoded);
}
import gif from 'omggif';
function parseGIF(image) {
const r = new gif.GifReader(image);
const data = [];
r.decodeAndBlitFrameRGBA(0, data);
const { width, height } = r.frameInfo(0);
return { width, height, data };
}
function decodeWithExternal() {
const gifBytes = encodeQR('Hello world', 'gif', opts);
const decoded = decodeQR(parseGIF(gifBytes));
console.log('decoded(gif)', decoded);
}
import { svgToPng } from '@paulmillr/qr/dom.js';
const png = svgToPng(encodeQR('Hello world', 'svg'), 512, 512);
Decoding options
export type Point4 = { x: number; y: number }[];
export type Image = {
height: number;
width: number;
data: Uint8Array | Uint8ClampedArray | number[];
};
export type DecodeOpts = {
isRGB?: boolean;
detectFn?: (points: Point4) => void;
qrFn?: (img: Image) => void;
};
export default function decodeQR(img: Image, opts: DecodeOpts = {});
Decoding algorithm
QR code decoding is challenging; it is essentially a computer vision problem. There are two main scenarios:
- Decoding from files: This can be slow because it needs to handle complicated cases such as blur or rotation.
- Decoding from a camera feed: This must be fast; even if one frame fails, the next frame can succeed.
The state-of-the-art approach for this, as with other computer vision problems, is using neural networks. However, using them would make the library hard to audit. Additionally, since JavaScript can't access hardware accelerators, it would likely be very slow. We also avoid using WebGL because it is complex and exposes users to fingerprinting.
The implemented reader algorithm is inspired by ZXing:
toBitmap
: Convert the image to a bitmap of black and white segments. This is the slowest part and the most important.
detect
: Find three finder patterns and one alignment pattern (for versions > 1). This is tricky—they can be rotated and distorted by perspective. A square might appear as a quadrilateral with unknown size. The best we can do is count runs of the same color and select patterns with almost the same ratio of runs.
transform
: Once patterns have been found, correct the perspective and transform the quadrilateral into a square.
decodeBitmap
: Execute the encoding in reverse: read information via a zig-zag pattern, de-interleave bytes, correct errors, convert to bits, and finally, read segments from bits to create the string.
- Finished!
Decoding test vectors
To test our QR code decoding, we use an excellent dataset
from BoofCV. BoofCV decodes 73% of the test cases,
while ZXing decodes 49%. Our implementation is nearly at parity with ZXing, primarily because ECI (Extended
Channel Interpretation) support is not yet included. The test vectors are preserved in a Git repository at
github.com/paulmillr/qr-code-vectors.
Note for Testing on iOS Safari: Accessing the camera on iOS Safari requires HTTPS. This means that the file: protocol or non-encrypted http cannot be used. Ensure your testing environment uses https:.
The QR code specification is available for purchase at iso.org for 200 CHF.
DOM helpers for web apps
Check out dom.ts
for browser-related camera code that would make your apps simpler.
Using with Kotlin
@JsModule("@paulmillr/qr")
@JsNonModule
external object Qr {
@JsName("default")
fun encodeQR(text: String, output: String = definedExternally, opts: dynamic = definedExternally): Uint8Array
}
val bytes = Qr.encodeQR("text", "gif", js("{ scale: 10 }"))
val blob = Blob(arrayOf(bytes), BlobPropertyBag("image/gif"))
val imgSrc = URL.createObjectURL(blob)
Security
There are multiple ways a single text can be encoded in a QR code, which can lead to potential security implications:
- Segmentation Differences: For example,
abc123
can be encoded as:
[{type: 'alphanum', data: 'abc'}, {type: 'num', data: '123'}]
or [{type: 'alphanum', data: 'abc123'}]
- Mask Selection Algorithms: Different libraries may use different algorithms for mask selection.
- Default Settings: Variations in error correction levels and how many bits are stored before upgrading versions.
If an adversary can access multiple QR codes generated from a specific library, they may be able to fingerprint the user. This fingerprinting could be used to exfiltrate data from air-gapped systems. In such cases, the adversary would need to create a library-specific exploit.
We mitigate these risks by:
- Cross-Testing: We currently cross-test against python-qrcode, which is closer to the specification
than some JavaScript implementations.
- Single Segment Encoding: We always use single-segment encoding.
While this may not be the most optimal for performance, it reduces the amount of fingerprinting data.
Future plans:
- Testing Against Multiple Libraries: To further improve security and reduce fingerprinting, we can
cross-test against three to four popular libraries.
Speed
Benchmarks measured with Apple M2 on MacOS 13 with node.js 19.
======== encode/ascii ========
encode/paulmillr-qr x 1,794 ops/sec @ 557μs/op
encode/qrcode-generator x 3,128 ops/sec @ 319μs/op ± 1.12% (min: 293μs, max: 3ms)
encode/nuintun x 1,872 ops/sec @ 533μs/op
======== encode/gif ========
encode/paulmillr-qr x 1,771 ops/sec @ 564μs/op
encode/qrcode-generator x 1,773 ops/sec @ 563μs/op
encode/nuintun x 1,883 ops/sec @ 530μs/op
======== encode: big ========
encode/paulmillr-qr x 87 ops/sec @ 11ms/op
encode/qrcode-generator x 124 ops/sec @ 8ms/op
encode/nuintun x 143 ops/sec @ 6ms/op
======== decode ========
decode/paulmillr-qr x 96 ops/sec @ 10ms/op ± 1.39% (min: 9ms, max: 32ms)
decode/jsqr x 34 ops/sec @ 28ms/op
decode/nuintun x 35 ops/sec @ 28ms/op
decode/instascan x 79 ops/sec @ 12ms/op ± 6.73% (min: 9ms, max: 223ms)
======== Decoding quality ========
blurred(45): paulmillr-qr=12 (26.66%) jsqr=13 (28.88%) nuintun=13 (28.88%) instascan=11 (24.44%)
License
Copyright (c) 2023 Paul Miller (paulmillr.com)
Copyright (c) 2019 ZXing authors
The library @paulmillr/qr is dual-licensed under the Apache 2.0 OR MIT license.
You can select a license of your choice.
The library contains code inspired by ZXing, which is licensed under Apache 2.0.
The license to the use of the QR Code stipulated by JIS (Japanese Industrial Standards) and the ISO are not necessary.
The specification for QR Code has been made available for use by any person or organization. (Obtaining QR Code Specification)
The word “QR Code” is registered trademark of DENSO WAVE INCORPORATED in Japan and other countries.
To use the word “QR Code” in your publications or web site, etc, please indicate a sentence QR Code is registered trademark of DENSO WAVE INCORPORATED.
This registered trademark applies only for the word “QR Code”, and not for the QR Code pattern (image).
(https://www.qrcode.com/en/faq.html)