A brighter display with higher contrast is more likely to work reliably with certain barcode scanners. For example, I sometimes struggle to get my Tesco Clubcard QR code (edit: actually an Aztec code) to scan on their old (red laser) self-checkout machines with my iPhone, but on my Apple Watch it displays brighter and seems to work more reliably.
Every time I'm queuing somewhere that requires scanning QR codes or digital barcodes, I see some people going through the back-and-forth of scans not working and the person fiddling with their brightness settings or fighting auto-brightness. I'd say there's a legitimate use case for this right there.
Haven't flown in a few years but I flew a ton 2017-2020 and airlines could never scan the barcode on an eTicket if I forgot to turn the brightness up all the way. I'm guessing it is more because of glare than contrast though if that makes you feel any better.
Airline barcodes aren't QR codes. They are Aztec codes or PDF417 codes, and software for reading them is generally less robust and less smart because less investment has gone into clever ways to align the codes quickly. The codes themselves also have less good alignment markers, especially for dealing with lens distortion.
Phones typically have glossy screens which can be a real problem if there are light sources in the sourrundings that can be reflected - including the scanner's own lights which, yes, should be turned off when scanning a phone barcode but this is not always the case in practice. Upping the brightness of the phone display itself mitigates this.
Phone screens are awfully flat though - which means glare from a light is typically a small area. QR codes are robust to small areas being missing. In fact, a typical QR code is readable with about 20% of the code missing.
I've been doing some work in this space (eticketing) and it's not as easy as you think. OK, 95% of the time it works, but that's not good enough and when you move into the "real world" - cracked screens, smudges, glare, dirty sensors it gets worse. The failure cases waste a huge amount of time.
Exactly. QR code scanning abilities of new smartphones has gotten so incredibly quick at scanning the code. I barely point my iPhone 14 Pro's camera at the code and it already scans and displays the information. Even with the motion blur on the camera as I'm pointing the phone at the code.
I think the focus should be more on the ability to interpret damaged codes via ML capabilities as most QR codes are outdoors.
Scanning an on-screen QR code is usually done with barcode scanners, not with phones. Typically, barcode scanners are doing the decoding on-device, and passing out keyboard data (their drivers usually identify them as USB HID). Unfortunately, most scanners don't have loads of onboard processing power, though ability to deal with damaged linear barcodes has been quite good for a long time. Damaged 2D barcodes are harder to deal with, and while ML may be able to solve that, it would require a paradigm shift in how barcode scanners operate -- and essentially bifurcate the market, as some scanners would simply no longer be compatible with embedded systems, and would require specialised software to function (which isn't really ideal; most users of barcode scanners want them to be plug-and-play).
(My first post-university job was doing tech support for a company which sold point-of-sale equipment. I'd say about 50% of my job was helping people with barcode scanners.)
