Intelligent video’s expanding presence in all sorts of applications is driven by several factors: the shift from analog to digital sensing; improved wired and wireless networking; and more sophisticated software. The latest systems push beyond basic image sensing and capture capabilities to image analysis, thanks to powerful video-processing hardware and intelligent video software.
Today’s intelligent cameras are replacing yesterday’s PCbased systems in terms of functionality. These ever-shrinking cameras feature faster and higher-bandwidth connections between their outputs and other circuits, with some functions on the sensing chip and many more functions within the box or housing itself. Previously, such functions required an external PC platform or a host computer for processing.
From the business side, intelligent video has become a matter of practicality. In manufacturing, it’s virtually impossible to examine products coming off a high-speed production line for quality and defects without using intelligent video systems. In surveillance, security personnel viewing a monitor at an airport or other public facility face the dual challenge of spotting the bad guys while fighting off boredom.
Intelligent video-surveillance systems aren’t just more vigilant, they’re also more accurate. With their greater intelligence, they can discern nuances in observed individuals and make the necessary critical analyses and judgments that are difficult if not impossible for a human operator.
In addition to getting more intelligent by using on-chip or in-the-camera-box hardware and software, video cameras can support downloadable modules produced by third-party vendors. Some companies offer totally integrated camera solutions, while others allow for more flexibility. Flexibility in this case means that the user can fine-tune the camera system to observe and track a specific type of object or objects for specific features. The trend is to gather a small amount of data at high speed from the camera sensor for further analysis down the line, leading to a more intelligent analysis of what is being viewed.
VIDEO INTELLIGENCE IS BIG BUSINESS
Major cities in the U.S. and other countries now use sophisticated video-surveillance technology to improve their security infrastructure. Chicago, Ill., for instance, has partnered with IBM to implement a smart video-surveillance network that’s been dubbed the most advanced of its kind in the U.S. It can alert officials whenever it detects a specific vehicle’s license-plate number, observes a vehicle circling a specific location, or spies an unattended object.
“Video surveillance is the fastest-growing market for digital video chip providers,” says Chris Day, president and CEO of Mobilygen. According to the China Security Market Report issued by the Security Industry Association, China’s video security and protection market (including fire and safety monitoring, security surveillance, and access control) is projected to jump from $6.3 billion in 2005 to $18 billion by 2010.
TWO APPROACHES
Broadly speaking, there are two types of intelligent camera systems: smart or IP cameras and embedded systems. Smart cameras integrate the camera sensor and the processing circuitry. In embedded systems, the video sensing is in one location. It’s connected either wirelessly or by wire to an embedded system elsewhere that consists of a frame-grabber board and a processor external to the camera sensor.
These differences are narrowing, though. Some smart cameras have so much intelligence, either on the sensing chip or within the same case holding the chip, that many of their manufacturers consider them embedded systems. However, the application usually dictates the type of camera system needed.
Smart cameras are more useful in space-challenged applications, but typically they don’t have as much processing power as the embedded approach. Although they’re generally less expensive than embedded camera systems, that cost advantage can quickly evaporate when using multiple cameras.
An embedded approach will offer greater programming flexibility and becomes a very desirable option for applications in which multiple cameras are used to view many scenes. Moreover, it can support a wide range of cameras from different manufacturers , which is another space-saving feature because one embedded unit can service multiple cameras. On top of that, it provides more freedom when choosing a camera signal’s interface.
Leutron Vision’s LVmPC micro PC uses the embedded approach to save space in embedded vision applications. It combines innovative notebook and frame-grabber technologies in a small 91- by 92- by 182-mm footprint. Designed for popular operating systems like Windows, Linux, and VxWorks, it uses Intel’s ultra-low-power Pentium III and Celeron processors.
Another space-saver is the CCD-based (charge-coupled device) In-Sight Micro smart camera from Cognex, which measures just 30 by 30 by 60 mm (Fig. 1). It’s designed for mounting in tight spaces on robots, production lines, and machinery. A flexible mounting capability with a non-linear calibration tool allows for mounting at angles up to 45° for hard-to-reach applications.
Most machine-vision cameras use CMOS sensors in applications where low cost is important and performance isn’t demanding. CCD imagers, though, dominate applications that require high performance (see “Choosing An Image Sensor: It’s All About The Application” at www.electronicdesign.com, Drill Deeper 18801). Roughly half of all image sensors are analog, with the other half being digital. Both types have driven the trend toward smaller machine-vision cameras.
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