Camera pricing

Point Grey sent me an email – you probably got it too – saying that the latest additions to their Flea series are priced at $995.

I haven’t purchased a machine camera for a while, but that strikes me as a competitive price for a 2.8Mp GigeE unit with a Sony CCD sensor. Time was I used to calculate the price per megapixel – call it the Grey Index – and just last year I was paying $500 per Mp. This camera, the FL3-GE-28S4C or S4M if you want the monochrome version, works out at $335 per Mp.

Cameras keep getting cheaper.

Interesting new camera

Point Grey has just announced an 8.8 Mp version of their compact Flea 3 USB 3.0 camera. Inevitably, packing an array of 4096 by 2160 pixels into a C-mount format sensor means the pixels are pretty darned small, and that’s where this is interesting.

This hi-res Flea 3 is using a Sony IMX121 color sensor with pixels just 1.75 microns in size. On learning that, my first thought is “poor sensitivity and high noise,” but that might not be the case. Sony are making a big deal of their “Exmor R” CMOS sensor technology that effectively switches the positions of the internal wiring and the photon-capturing silicon. (Click the link to see a great animation of how it works.)

This, it is claimed, increases sensitivity by 6db and reduces noise by 2db. Those might not seem big numbers but remember that it’s all logarithmic. Sony has one comparison image posted on their site; it would be interesting to see a few more.

Two last points to mention: the camera puts out 21fps at full resolution, which is a pretty impressive number. Good thing USB 3.0 offers 5Gbits per second of bandwidth! And pricing? $945, which seems like a bargain.

Sensor data

When you are selecting a camera it’s always prudent to find out what sensor the manufacturer is using. Then take a look at the quantum efficiency graph. This shows the relative sensitivity of the sensor to wavelengths of incident light and may influence your choice of illumination. Not all sensors are the same!

The problem though is that while some camera vendors make this information available – AVT is one such – it can be hard to find what you need. And for some reason this seems particularly true when Sony sensors such as the ICX625 are involved.

But I have good news! (Well, a small portion of good news anyway.) Point Grey have some quantum efficiency data in the knowledge base area of their website. This covers Sony CMOS and CCD sensors as well as CMOS sensors from Aptina and Cmosis. Take a look! It’s free!

Color camera technology

CCD and CMOS sensors put out electrons in response to photons that land on their silicon surface. They have no knowledge of the wavelength of the light that fell on them. So how, you might be wondering, does the camera know when to put out red, green or blue?

Well most color cameras use a Bayer filter over the CCD sensor. This red, green and blue mosaic filters photons by color so that some pixels only receive red, some blue and the rest green. In fact I thought that was the way all color cameras did things, but thanks to an article on the Basler web site, I now know better.

“Color Creation with Interlaced Sensors – How Does That Work?” describes how the Sony ICX409 sensor creates color images. What’s interesting is that it uses a four color filter – green, magenta (pink), cyan (blue) and yellow – and a complex binning process to produce color images. There’s some good detail in the article, so if this is something that interests you, take a look.

A prediction for machine vision lenses

It seems like yesterday that a 2Mp sensor was “high resolution” but today 5Mp is the new 2Mp and I’m pretty sure that in another year or so 12Mp will be on its way to commonplace. Much of this is driven by the consumer camera market where megapixels sell, but it’s fair to say that in machine vision we want higher resolution too.

Now if you study sensor specs you’ll know that as pixel numbers go up, each pixel gets smaller. If it didn’t we’d have image sensors the size of tennis courts by now! But I think there’s a limit to how small pixels can get.

The first issue is noise. As pixels get smaller so does their “full well capacity,” yet because noise is proportional to the square root of numbers of photons captured, smaller pixels tend to exhibit more noise.

Second, there’s that pesky business of diffraction. If you go back to my post of February 8th, 2009 (Wavelength matters,) you’ll see reference to something called the Airy disc. What this means is that light can’t be focused down smaller than its wavelength. Now as red is around 0.660 µm, that pretty much sets a limit on how small a pixel can be.

Right now it seems that most sensors used in machine vision – like the 5Mp Sony ICX625 - have pixels of 3.5 µm or greater, but consumer applications are already edging into the sub micron area. For the reasons listed above, that’s not going to work for us, so what’s the conclusion?

Well that brings me to my prediction: as resolutions increase we’re going to reach the point where the trusty C-mount lens will no longer do the job. Quite simply, we will have to use larger format lenses (I’m thinking F-mount,) to project our images onto the larger CCD and CMOS sensors that we’ll want to use.

In other words, large format lenses could be a real growth area a couple of years from now.

Cognex ratchets up the resolution

I’m a little surprised how long it took, but Cognex finally got around to releasing a 5 megapixel version of their In-Sight smart camera, the 5605. Specs are sketchy, to say the list. There’s a single sentence on the In-Sight product page, but no indication of frame rate or the processor employed.

For me those two factors are critical in deciding whether to actually deploy vision applications on the 5605. All the resolution in the world is no good to me if I can’t capture enough images or can’t finish processing one before the next arrives.

But I suspect those points will be moot when I find out the price. I doubt this little baby is much below $9K, which means that I could save a pile by going with a PC-based solution, perhaps using a camera like the Pike from AVT, (which I’m guessing has the same Sony ICX625 sensor as the 5605,) coupled with Cognex VisionPro.

Scorpion rumor

I hear that Scorpion are looking to put their 3D software on the Sony smart camera. If true, this will have them going head-to-head with Sick in the industrial 3D camera business.

As I understand things, this will be part of the upcoming release of Scorpion Vision Version 7.2. No word on pricing, although I anticipate something upwards of €6000 for the full camera+software bundle. Scorpion isn’t the cheapest machine vision software package out there, but founder Thor Vollset is working hard to establish his software product as a credible alternative to Cognex VisionPro and Halcon from MVTec.

If you’re looking for a standard machine vision platform you could do a lot worse than to consider this Scandinavian startup.

Pixel pitch and pixel spacing

In “MTF and high resolution sensors” I discussed the impact of pixel pitch on resolution. Having received a question on this, I’d like to explain briefly why its pixel pitch that matters and not pixel size (although they are of course related,) and tell you where to find the information.

The size of a pixel gives you an indication of its light-receiving area. However, in discussing resolution it’s the spacing between the pixels that matters. The equation is:

Fmax-practical = 1/(4 x pixel pitch)

Where Fmax-practical is the maximum line-pair frequency that the sensor can resolve.

I gave the example of the 5Mp Sony ICX625 CCD which has pixels of 3.45 microns. However, the pixel pitch is around 4 microns. Why is the pitch greater than the pixel size? Well not all of the silicon collects light. In effect, there’s a border around each pixel, or to put it another way, there’s a space between neighboring pixels.

To determine the pitch you need the dimensions of the active region of the CCD, and for that you need to sensor’s spec sheet. Strangely, I couldn’t find it on Sony’s web site – they seem to want to keep it secret – but it's out there if you look hard enough. Once you've tracked it down you'll learn that the ICX625 measures 9.93 mm in the horizontal direction, and there are 2448 pixels in that length, which is how we get the pixel pitch of 4 microns. As a sanity check, you could do the following: given that the sensor is a 2/3” format with a 4:3 aspect ratio and a diagonal of 11.016mm, work out the length of the sides and calculate the pitch from there.

Hope that makes things clear. And by the way, I do welcome comments, so if you’ve got questions, complaints or anything you want to share, please make use of the “Comment” function.

Take a closer look

Sometimes a really nice product comes along that just seems unable to gain any traction in the marketplace. Everyone looks at it and says, “Yes, that’s neat, I could use it,” but then fails to put their money where their mouth is.

Such a product is the family of Sony smart cameras. They run XP embedded, so they’re basically a PC in a box, and with Halcon able to run on the latest models, you’ve got the power of a high-end vision system in a compact, production line-ready, package.

Halcon, by the way, is another underappreciated product, in North America anyway. (I think it sells much better in Europe.) Developed by MVTec of Germany, Halcon is certainly comparable to products like Matrox MIL, Sapera and VisionPro. If you need the power of a PC-based vision system and the form factor and convenience of a smart camera, this combination might be worth considering.