williamlweaver, glad you will be joining us. I think that's an intriguing point about all the photoshopping of the (soon-to-be) massive amounts of online photos. Might make a good question for our lecturer.
Lou, glad you will be joining us. In the time I spent reporting on machine vision, I discovered that there really isn't a single MV industry anymore, and within it there are multiple trends, sometimes apparently opposite ones. While some vision system/production system designers are shifting more toward distributed control, others are moving toward centralized control. And these differences exist not only between application clusters within traditional industrial machine vision, but within them, too. It all depends on what the vision system is being required to do and what constraints there are on it. At a larger scale, the formation of the EVA made it clear that things are even more complex when you go outside industrial machine vision and look at other uses of embedded computer vision.
Thanks @Ann! Embedded Vision is a very timely topic. With inexpensive vision sensors being place in all sorts of devices we are moving beyond the technology of "how can we do this?" and into "how can we use this?" ...and soon after "why do we need this?". One of the largest immediate impacts will be its disruptive effect on police sketch artists and eyewitnesses. With every action digitally recorded, we will move quickly away from the "he said", "she said" impasses of yesteryear.
On the positive employment side, the demand for "video-photo-shoppers" will skyrocket, both for vanity's sake and for those underworld characters that have enough money to alter the photographic record.
Ann, this is an interesting contrast to the article from August 13, by Al Presher, titled "Blurring the Lines of Control". In that article, the machine control system integrated image processing with other functions in a centralized computer. As I commneted then, this is going against the trend in the industry, as mentioned in this article, for distributing the intelligence. For example, a modern automobile has probably 50 or more processors. Genreally there is even a processor for the temperature guage. It is cheaper to do that than to integrate software on a centraized machine. In addition, it is generally more accurate when performing control functions to have the processing near the device.
I am looking forward to Jeff's course as well. It should be interesting.
Truchard will be presented the award at the 2014 Golden Mousetrap Awards ceremony during the co-located events Pacific Design & Manufacturing, MD&M West, WestPack, PLASTEC West, Electronics West, ATX West, and AeroCon.
In a bid to boost the viability of lithium-based electric car batteries, a team at Lawrence Berkeley National Laboratory has developed a chemistry that could possibly double an EV’s driving range while cutting its battery cost in half.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.