Making the Move to Digital in Machine Vision
- Sunday, 01 March 2009
A side benefit of in-camera preprocessing is that it does not affect the system interfaces or hardware design. The camera can achieve its preprocessing by routing the sensor data through an FPGA for manipulation before passing it on to the rest of the system. From a system design standpoint, all that changes is the interpretation of the data coming in. In many cases, preprocessing can eliminate tasks that would otherwise be handled in the image processor, reducing processing demands and increasing system performance.
As a result of these innovations and the inherently digital nature of the image data, digital cameras provide vastly greater design flexibility and simpler system design than analog cameras. By ensuring that pixels are automatically square and reliably represent the same point on the image every frame, digital cameras eliminate the calibration that analog cameras require for their digitizers. Similarly, digital cameras can handle white balance calibration automatically while analog systems require manual calibration in both the camera and frame grabber.
The use of digital cameras also simplifies system design by supporting the easy implementation of configuration options. Changing the image resolution of an analog camera machine vision system, for instance, also forces timing changes in the frame grabber and alters the digitizer clock speed. To recalibrate and resynchronize the system to the new camera requires considerable frame grabber expertise. Changing digital system resolution, on the other hand, involves only replacing the camera and altering the data clocking rate, with perhaps some software modification to handle the new data structure.
Digital camera systems are also easier to set-up and maintain. While analog systems require coordination between camera and frame grabber, both of which are have independent controls, all elements of a digital camera system can be controlled from the PC used for image processing.
Adopting Digital Reduces Costs
All the advantages that digital cameras with GigE interfaces offer machine vision systems makes them a logical choice for new designs, despite their price premium of about 20% over comparable analog cameras when such analog cameras of sufficient performance are available. But digital cameras also make sense as an upgrade step for existing vision systems. While many legacy analog camera vision system applications will never require the high performance obtainable only with digital cameras, performance is not the only reason to upgrade.
There are several triggering events that can justify making the investment to replace analog camera machine vision systems with digital ones. One is a change in system performance requirements that analog systems cannot readily handle. A desire to increase the throughput of a visual inspection system, which is set by the camera frame rate, may require performance beyond the range of analog cameras. A new need for color vision can also prompt movement to a digital camera for its greater simplicity and minimal calibration requirements.
The need to replace failing components or ones that have become obsolete can be another triggering event. Most of the new development in electronics concentrates on digital systems, so a replacement for an obsolete analog camera that offers equivalent or better performance may be difficult to find.
It may also be appropriate to replace an analog camera vision system in order to reduce the cost and complexity of system maintenance. Analog systems require frame grabbers and specialized interface cards on the host PC to allow transfer of data out of the frame grabber. Digital systems no longer require frame grabbers. Data storage occurs either in the camera or in the host PC. Further, with GigE, the camera interface is already built into an off-the-shelf PC so no specialized hardware is needed.
This article was written by Yvon Bouchard, Director of Systems Architecture at DALSA, Montreal, QE, Canada.