Machine-vision focus shifts with application

By Rick Nelson, Chief Editor -- Test & Measurement World, 2/1/2008

Dalsa sales and marketing VP Philip Colet commented on hot topics in the machine-vision industry in this interview with T&MW.

A. When I look at machine vision, I look at the different components: lighting, optics, sensor technology, camera technology, data-acquisition technology, and image analysis and processing. Depending on the type of application a customer has, we will stress different components in different ways. In terms of illumination for semiconductor applications, as line widths get smaller and smaller, we want to start talking about ultraviolet (UV) and deep UV, and that has implications for optical technology and sensor technology. And since the data rates are so high, there are also implications with respect to camera speed and data processing.

Q. Where is the emphasis on printed-circuit board (PCB) inspection applications—on frame rates and resolution or on algorithms that can do more with less data?

A. In automated optical inspection [AOI] applications, the throughput of a machine is a competitive advantage, so the faster that machine works, the better. The machine must, of course, analyze the images it acquires, but it all comes down to how quickly it can scan a PCB and how many PCBs it can do in an hour. So, the AOI OEMs are asking for higher resolution, and they are asking for higher frame rates.

Q. Dalsa recently introduced the Falcon 1.4M100 area-scan camera. What are some of its features?

A. Its resolution of 1400-by-1k pixels is good for a variety of machine-vision applications. Also, the size of the sensor ties in nicely to the size of available lenses, so you can use a relatively inexpensive lens, and you can get relatively close to your object.

But the unique feature about this camera is the speed—the ability to go to 100 fps at that resolution. And that speed of image acquisition can be useful in, for example, the populated PCB AOI we were just discussing. It can also find use in the high-speed chip shooters that are populating PCBs.

Q. Is it a CMOS or a CCD camera?

A. It’s a CMOS sensor that provides very good quality images with quite a good signal-to-noise ratio as well as quite good CCD-quality light-gathering capability. The whole debate about CMOS vs. CCD is to us almost irrelevant. To us, the image quality we can get with a CMOS sensor is just as good as what we can derive with many CCD imagers on the market today.

Q. So CMOS will replace the CCD?

A. CCD won’t go away. There will continue to be niche applications for CCD—for example, for applications requiring backside thinning. Backside thinning is a lot easier to do with CCDs than with CMOS.

A second example is the TDI [time delay and integration] sensor. Dalsa makes a lot of TDI sensors, which are essentially line-scan sensors where you have this bucket brigade in which you are dumping charge. With CMOS, that just doesn’t happen, because you don’t have a charge anymore, you have a voltage, and you can’t really accumulate voltage the way you can accumulate charge.

So our feeling is, CCD will stay in these niche applications, but CMOS will take over in terms of image quality.

Q. What’s happening with image processing—is it still taking place on a dedicated image-processing board, or is it migrating to the PC?

A. If you go back 15 years, you had relatively lame computers, and all of the processing had to occur on special image-processing hardware. But then two things happened. Number 1, the PCI bus became popular, and it allowed you to dump raw data down to a PC. And number 2, we saw a corresponding rise in the processing power of the PC. It was those two things happening at the same time that enabled a transfer of processing responsibility from an onboard architecture down to a standard PC architecture.

Q. So, the embedded architecture is dead?

A. No way. Because people are always pushing the envelope. The kinds of sensors that are coming out right now, the data rates they are running at, and the complex algorithms that people want to execute can still overwhelm even a quad-core PC, so you still have to do some processing on the board. Where do we find those applications? They tend to be in anywhere you are generating a lot of data—such as semiconductor wafer-inspection applications—or they tend to be in real-time applications, where I do not have the ability to accumulate data and then process it.

Q. What will be the hot topics in machine vision in 2008?

A. The debate will continue between CCD and CMOS, and I expect CMOS to continue to progress in terms of image quality and light sensitivity. In terms of camera technology, I expect the issues to have more to do with the interconnect as opposed to what’s in the camera itself.

The hot subjects there would be where we are in terms of 10 GigE Vision and where we are in terms of Camera Link and its limitations. We have the mini-Camera Link connector now and Power over Camera Link, which are real benefits to OEMs, but what comes next?

Camera Link will bring you up to about 680 Mbytes/s maximum, but we are talking about sensors that will be going at 1 Gbyte/s or even 2 or 3 Gbytes/s. What interconnect technology are we going to be using for them? We will be looking at PCI Express to see what it can do for us.

In terms of software technology, there will be continued work on pattern recognition and on color. Today, color is complicated because there are a lot of ways to look at color, and color tools now are somewhat antiquated in how they force people to think about color. New color tools should simplify the life of the OEMs so they are not forced into thinking in one domain or another.