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Eight Considerations When Evaluating a Smart Camera

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By Carlton Heard
Product Engineer – Vision Hardware and Software
National Instruments

With the increase in performance and decrease in cost, smart cameras have become increasingly more accessible over the past decade. Given this trend, how do you determine which smart camera best meets your needs or decide if a smart camera is appropriate for your application? Learn about the top 8 considerations you don't want to forget when selecting a smart camera, including application examples and alternative solutions.

Smart cameras have been around for many years, but advances in processor technologies have made smart cameras much more accessible and popular within the past decade, especially in applications such as machine vision and surveillance. However, when the term smart camera is mentioned, a wide variety of ideas still come to mind, because there is no widespread agreement on the technical definition of just what a smart camera is.

It is generally agreed that the basics of a smart camera includes not only the image sensor, but also some type of processing chip. This can be a CPU, DSP, FPGA, or other type of processing device. However, today even an off-the-shelf point & shoot digital camera has some type of built-in image processing, for example to make the image look more desirable, remove red eye effects, conduct facial recognition, and/or other types of image processing.

So, if the inclusion of a processor along with an image sensor isn’t the defining attribute of a smart camera, what makes a smart camera “smart”? They key lies in the output. Unlike most cameras, the primary output of a smart camera is not an image but a decision or some other type of information (Figure 1). Since the image processing or machine vision algorithm is...

Eric Gregori
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There is a good whitepaper covering NI's Labview and Vision Builder tools for various computer vision applications.