If there is no sticker, the buyer has to search through oodles of strangely organized* pictures on a display, to select the item, before it can be weighed or the quantity entered manually.
When I used to live in France, they, too, made me go through oodles of strangely organized pictures, so that I can put my produce on a scale, weigh it and put a price sticker, and THEN, i can finally bring it to a cashier. The worst shopping experience ever in the French supermarket. (I can see pictures alright, but if I didn't know the name of produce in French, it took me forever to spot the right picture!)
But at any rate, I had not thought about this in a way you did. (you are smart) Why wouldn't we make a scanner (with an image sensor) that can also actually see and recognize shapes and colors of produce? Certinaly possible, isn't it?
Not only that, but smaller pixels to achieve those higher pixel counts means less signal and lower signal to noise ratio = lower dynamic range. That said, I am really impressed with the pictures I can take with my Samsung Galaxy S4 smartphone! My wife too, and she's always borrowing it because it takes at least as good pictures as her Fujifilm digital SLR, and much better than her low-end Samsung smartphone. I'm not so impressed with the low-light capability; no doubt those smaller pixels and the millimeter-sized lens don't help.
Speaking of optical dynamic range, when is somebody going to come up with liquid crystal sunglasses? Forget the photochromic glasses; they are too slow, they don't get dark enough, and they don't work in the car because they're only sensitive to ultraviolet light, and the window glass blocks UV. I want glasses with a knob I can turn to darken them when I go outside and lighten them back up when I come inside again. Don't forget the human in the loop! Duh!
I think your point about uses being only limited by one's imagination is right on target, Junko.
One application I've wondered about is the supermarket self checkout. Most items you buy have a bar code, so fair enough. But some items, like produce, either have a little sticker-cum-bar code glued on them, or nothing at all. If there is no sticker, the buyer has to search through oodles of strangely organized* pictures on a display, to select the item, before it can be weighed or the quantity entered manually.
Why? We can see it and recognize it, can't we? Why can't the machine do the same?
I think it's revealing to see that license plate and road sign reading software is becoming available. It's an interesting trend. Instead of having to change these legacy systems to make them machine readable, we change the machines to make them capable of reading signs designed for human consumption.
On the megapixels hype, also a good point. The simplest way to describe why is this. The lens focuses the image on the sensor. A cheap or too-small lens often does not have the resolution to make use of a very tight arrangement of pixels in the sensor. Lens blur will not allow much differentiation in the light impacting adjacent pixels, so the beneficial effect of more tightly spaced pixels cannot be exploited. A better lens, and/or a larger image sensor that spreads the pixels apart, is often a more meaningful improvement than just pixel count.
* Are green beans listed under G, or under B? Oddly, sometimes under B (beans, green). Are zucchini listed under z or under s? Oddly, even if they are labeled "squash" on the shelf, they might be listed under z in the checkout machine.
I find what machine vision has accomplished over the years astounding. Much of it, of course, has much to do with the advancements of analytic software, but what image sensors are capable of caturing today is also equally amazing.
Now that machine visions are getting gout of a factory floor to a street, I'd say image sensor battle has now well passed the megapixel race.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.